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authorGian Marco Iodice <gianmarco.iodice@arm.com>2019-07-19 09:54:47 +0100
committerGian Marco Iodice <gianmarco.iodice@arm.com>2019-07-23 15:01:41 +0000
commitd1f54767fc9d6398a5eea38e639dd0ce3df8e5d8 (patch)
tree0e271b739fe9144c22a8cc05852e3fc28db88a7a /src
parent5f98d74892468b944246e60c5a70ad84a7c6bbc9 (diff)
downloadComputeLibrary-d1f54767fc9d6398a5eea38e639dd0ce3df8e5d8.tar.gz
COMPMID-1979: Fuse Activation Function in CLGEMM - part 3
Fused beta*bias in in the old cl gemm kernels Fused activation function in the old cl gemm kernels Change-Id: I695fb9189e6d4792010abd256784624982d17d79 Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Reviewed-on: https://review.mlplatform.org/c/1587 Reviewed-by: Giuseppe Rossini <giuseppe.rossini@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src')
-rw-r--r--src/core/CL/cl_kernels/gemm.cl2181
-rw-r--r--src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp133
2 files changed, 1198 insertions, 1116 deletions
diff --git a/src/core/CL/cl_kernels/gemm.cl b/src/core/CL/cl_kernels/gemm.cl
index 213075df07..8d638bc6bb 100644
--- a/src/core/CL/cl_kernels/gemm.cl
+++ b/src/core/CL/cl_kernels/gemm.cl
@@ -46,15 +46,15 @@
/** This OpenCL kernel reshapes the lhs input matrix. The kernel splits the input matrix in blocks of size M0xK0 and stores each one (not transposed) in
* the output matrix unrolling the values.
*
- * @note The data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=float)
- * @note The width of the input tensor must be passed at compile time using -DSRC_WIDTH (i.e. -DSRC_WIDTH=16)
- * @note The block's dimensions (M0 and K0) must be passed at compile time using -DM0 and -DK0 (i.e. -DM0=2, -DK0=2).
- * @note The number of M0xK0 vertical blocks to store on the same output row must be passed at compile time using -DV0 (i.e. -DV0=2)
+ * @note The data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=float)
+ * @note The width of the input tensor must be passed at compile time using -DSRC_WIDTH (e.g. -DSRC_WIDTH=16)
+ * @note The block's dimensions (M0 and K0) must be passed at compile time using -DM0 and -DK0 (e.g. -DM0=2, -DK0=2).
+ * @note The number of M0xK0 vertical blocks to store on the same output row must be passed at compile time using -DV0 (e.g. -DV0=2)
* @note Only the following values for M0, K0 and V0 are supported:
* M0: 2,3,4,5,6,7,8
* K0: 2,3,4,8,16
* V0: greater than 0
- * @note In case the input has to be reinterpreted as a 3D tensor (i.e. input of convolution layer 1x1), the following information must be passed at compile time:
+ * @note In case the input has to be reinterpreted as a 3D tensor (e.g. input of convolution layer 1x1), the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
* -# HEIGHT_GEMM3D: The height of the input in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the input in case it has to be reinterpreted as a 3D tensor
@@ -246,15 +246,15 @@ __kernel void gemm_reshape_lhs_matrix_nt(TENSOR3D_DECLARATION(src),
/** This OpenCL kernel reshapes the lhs input matrix. The kernel splits the input matrix in blocks of size M0xK0 and stores each one (transposed) in
* the output matrix unrolling the values.
*
- * @note The data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=float)
- * @note The width of the input tensor must be passed at compile time using -DSRC_WIDTH (i.e. -DSRC_WIDTH=16)
- * @note The block's dimensions (M0 and K0) must be passed at compile time using -DM0 and -DK0 (i.e. -DM0=2, -DK0=2).
- * @note The number of M0xK0 vertical blocks to store on the same output row must be passed at compile time using -DV0 (i.e. -DV0=2)
+ * @note The data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=float)
+ * @note The width of the input tensor must be passed at compile time using -DSRC_WIDTH (e.g. -DSRC_WIDTH=16)
+ * @note The block's dimensions (M0 and K0) must be passed at compile time using -DM0 and -DK0 (e.g. -DM0=2, -DK0=2).
+ * @note The number of M0xK0 vertical blocks to store on the same output row must be passed at compile time using -DV0 (e.g. -DV0=2)
* @note Only the following values for M0, K0 and V0 are supported:
* M0: 2,3,4,5,6,7,8
* K0: 2,3,4,8,16
* V0: greater than 0
- * @note In case the input has to be reinterpreted as a 3D tensor (i.e. input of convolution layer 1x1), the following information must be passed at compile time:
+ * @note In case the input has to be reinterpreted as a 3D tensor (e.g. input of convolution layer 1x1), the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
* -# HEIGHT_GEMM3D: The height of the input in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the input in case it has to be reinterpreted as a 3D tensor
@@ -402,10 +402,10 @@ __kernel void gemm_reshape_lhs_matrix_t(TENSOR3D_DECLARATION(src),
/** This OpenCL kernel reshapes the rhs input matrix. The kernel splits the input matrix in blocks of size K0xN0 and stores each one (not transposed) in
* the output matrix unrolling the values.
*
- * @note The data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=float)
- * @note The height of the input tensor must be passed at compile time using -DSRC_HEIGHT (i.e. -DSRC_HEIGHT=16)
- * @note The block's dimensions (K0 and N0) must be passed at compile time using -DK0 and -DN0 (i.e. -DK0=2, -DN0=2).
- * @note The number of K0xN0 vertical blocks to store on the same output row must be passed at compile time using -DH0 (i.e. -DH0=2)
+ * @note The data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=float)
+ * @note The height of the input tensor must be passed at compile time using -DSRC_HEIGHT (e.g. -DSRC_HEIGHT=16)
+ * @note The block's dimensions (K0 and N0) must be passed at compile time using -DK0 and -DN0 (e.g. -DK0=2, -DN0=2).
+ * @note The number of K0xN0 vertical blocks to store on the same output row must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the K0xN0 blocks have to be interleaved, the option -DINTERLEAVE must passed at compile time.
* @note Only the following values for K0, N0 and H0 are supported:
* N0: 2,3,4,8,16
@@ -555,10 +555,10 @@ __kernel void gemm_reshape_rhs_matrix_nt(TENSOR3D_DECLARATION(src),
/** This OpenCL kernel reshapes the rhs input matrix. The kernel splits the input matrix in blocks of size K0xN0 and stores each one (transposed) in
* the output matrix unrolling the values.
*
- * @note The data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=float)
- * @note The height of the input tensor must be passed at compile time using -DSRC_HEIGHT (i.e. -DSRC_HEIGHT=16)
- * @note The block's dimensions (K0 and N0) must be passed at compile time using -DK0 and -DN0 (i.e. -DK0=2, -DN0=2).
- * @note The number of K0xN0 vertical blocks to store on the same output row must be passed at compile time using -DH0 (i.e. -DH0=2)
+ * @note The data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=float)
+ * @note The height of the input tensor must be passed at compile time using -DSRC_HEIGHT (e.g. -DSRC_HEIGHT=16)
+ * @note The block's dimensions (K0 and N0) must be passed at compile time using -DK0 and -DN0 (e.g. -DK0=2, -DN0=2).
+ * @note The number of K0xN0 vertical blocks to store on the same output row must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the K0xN0 blocks have to be interleaved, the option -DINTERLEAVE must passed at compile time.
* @note The option -DTRANSPOSE must passed at compile time.
* @note Only the following values for K0, N0 and H0 are supported:
@@ -1010,11 +1010,11 @@ __kernel void gemm_reshape_rhs_matrix_t(TENSOR3D_DECLARATION(src),
* The RHS is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is transposed
*
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
- * @note The GEMM's dimensions (M,N and K) must be passed at compile time using -DM, -DN and and -DK (i.e. -DM=52, -DN=30 and -DK=90)
- * @note The number of columns of LHS matrix must be passed at compile time using -DK (i.e. -DK=64)
- * @note The block's dimensions used for reshaping the RHS matrix (N0 and K0) must be passed at compile time using -DN0 and -DK0 (i.e. -DN0=8, -DK0=4).
- * @note The number of M0 rows to process must be passed at compile time using -DM0 (i.e. -DM0=2)
- * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (i.e. -DH0=2)
+ * @note The GEMM's dimensions (M,N and K) must be passed at compile time using -DM, -DN and and -DK (e.g. -DM=52, -DN=30 and -DK=90)
+ * @note The number of columns of LHS matrix must be passed at compile time using -DK (e.g. -DK=64)
+ * @note The block's dimensions used for reshaping the RHS matrix (N0 and K0) must be passed at compile time using -DN0 and -DK0 (e.g. -DN0=8, -DK0=4).
+ * @note The number of M0 rows to process must be passed at compile time using -DM0 (e.g. -DM0=2)
+ * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time.
* @note Only the following configurations of M0, N0 and K0 are currently supported:
* - M0 = 1, 2, 3, 4, 5, 6, 7, 8
@@ -1022,7 +1022,7 @@ __kernel void gemm_reshape_rhs_matrix_t(TENSOR3D_DECLARATION(src),
* - K0 = 2, 3, 4, 8, 16
* - H0 >= 1
*
- * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (i.e. -DACTIVATION_TYPE=RELU), A, B variables required by some activation functions and should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
@@ -1043,7 +1043,6 @@ __kernel void gemm_reshape_rhs_matrix_t(TENSOR3D_DECLARATION(src),
* @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes)
* @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped matrix
- * @param[in] bias_ptr (Optional)Pointer to the bias reshaped matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
* @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes)
@@ -1392,10 +1391,10 @@ __kernel void gemm_mm_reshaped_only_rhs_t(IMAGE_DECLARATION(lhs),
* The RHS is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is NOT transposed
*
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
- * @note The GEMM's dimensions (M,N and K) must be passed at compile time using -DM, -DN and and -DK (i.e. -DM=52, -DN=30 and -DK=90).
- * @note The block's dimensions used for reshaping the RHS matrix (N0 and K0) must be passed at compile time using -DN0 and -DK0 (i.e. -DN0=8, -DK0=4).
- * @note The number of M0 rows to process must be passed at compile time using -DM0 (i.e. -DM0=2)
- * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (i.e. -DH0=2)
+ * @note The GEMM's dimensions (M,N and K) must be passed at compile time using -DM, -DN and and -DK (e.g. -DM=52, -DN=30 and -DK=90).
+ * @note The block's dimensions used for reshaping the RHS matrix (N0 and K0) must be passed at compile time using -DN0 and -DK0 (e.g. -DN0=8, -DK0=4).
+ * @note The number of M0 rows to process must be passed at compile time using -DM0 (e.g. -DM0=2)
+ * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time.
* @note Only the following configurations of M0, N0 and K0 are currently supported:
* - M0 = 1, 2, 3, 4, 5, 6, 7, 8
@@ -1403,7 +1402,7 @@ __kernel void gemm_mm_reshaped_only_rhs_t(IMAGE_DECLARATION(lhs),
* - K0 = 2, 3, 4, 8, 16
* - H0 >= 1
*
- * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (i.e. -DACTIVATION_TYPE=RELU), A, B variables required by some activation functions and should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
@@ -1798,10 +1797,10 @@ __kernel void gemm_mm_reshaped_only_rhs_nt(IMAGE_DECLARATION(lhs),
* The RHS matrix must be reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the K0xN0 must be transposed
*
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
- * @note The GEMM's dimensions M and N must be passed at compile time using -DM and -DN (i.e. -DM=52 and -DN=90).
- * @note The block's dimensions used for reshaping the LHS matrix and the RHS matrix (M0, N0 and K0) must be passed at compile time using -DM0, -DN0 and -DK0 (i.e. -DM0=4, -DN0=8, -DK0=4).
- * @note The number of M0xK0 vertical blocks stored on the same output row of the reshaped LHS matrix must be passed at compile time using -DV0 (i.e. -DV0=2)
- * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (i.e. -DH0=2)
+ * @note The GEMM's dimensions M and N must be passed at compile time using -DM and -DN (e.g. -DM=52 and -DN=90).
+ * @note The block's dimensions used for reshaping the LHS matrix and the RHS matrix (M0, N0 and K0) must be passed at compile time using -DM0, -DN0 and -DK0 (e.g. -DM0=4, -DN0=8, -DK0=4).
+ * @note The number of M0xK0 vertical blocks stored on the same output row of the reshaped LHS matrix must be passed at compile time using -DV0 (e.g. -DV0=2)
+ * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (e.g. -DH0=2)
* @note If the M0xK0 blocks in the reshaped LHS matrix have been interleaved, the option -DLHS_INTERLEAVE must passed at compile time.
* @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time.
* @note Only the following configurations of M0, N0 and K0 are currently supported:
@@ -1811,9 +1810,9 @@ __kernel void gemm_mm_reshaped_only_rhs_nt(IMAGE_DECLARATION(lhs),
* - V0 >= 1
* - H0 >= 1
*
- * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (i.e. -DACTIVATION_TYPE=RELU), A, B variables required by some activation functions and should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
- * @note In case the output has to be reinterpreted as a 3D tensor (i.e. output of convolution layer), the following information must be passed at compile time:
+ * @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time:
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
@@ -2123,17 +2122,17 @@ __kernel void gemm_mm_reshaped_lhs_nt_rhs_t(IMAGE_DECLARATION(lhs),
* The RHS matrix is NOT reshaped
*
* @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time.
- * @note The GEMM's dimensions (M,N and K) must be passed at compile time using -DM, -DN and and -DK (i.e. -DM=52, -DN=30 and -DK=90)
- * @note The number of columns of LHS matrix must be passed at compile time using -DK (i.e. -DK=64)
- * @note The number of M0 rows to process must be passed at compile time using -DM0 (i.e. -DM0=2)
- * @note The number of K0 partial accumulations must be passed at compile time using -DK0 (i.e., -DK0=2)
- * @note The number of N0 columns to process must be passed at compile time using -DN0 (i.e. -DN0=2)
+ * @note The GEMM's dimensions (M,N and K) must be passed at compile time using -DM, -DN and and -DK (e.g. -DM=52, -DN=30 and -DK=90)
+ * @note The number of columns of LHS matrix must be passed at compile time using -DK (e.g. -DK=64)
+ * @note The number of M0 rows to process must be passed at compile time using -DM0 (e.g. -DM0=2)
+ * @note The number of K0 partial accumulations must be passed at compile time using -DK0 (e.g., -DK0=2)
+ * @note The number of N0 columns to process must be passed at compile time using -DN0 (e.g. -DN0=2)
* @note Only the following configurations of M0, N0 and K0 are currently supported:
* - M0 = 1, 2, 3, 4, 5, 6, 7, 8
* - N0 = 2, 3, 4, 8, 16
* - K0 = 2, 3, 4, 8, 16
*
- * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (i.e. -DACTIVATION_TYPE=RELU), A, B variables required by some activation functions and should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
* The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
@@ -2154,7 +2153,6 @@ __kernel void gemm_mm_reshaped_lhs_nt_rhs_t(IMAGE_DECLARATION(lhs),
* @param[in] rhs_stride_y Stride of the RHS matrix in Y dimension (in bytes)
* @param[in] rhs_step_y rhs_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS matrix
- * @param[in] bias_ptr (Optional)Pointer to the bias reshaped matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
* @param[in] bias_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
* @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes)
@@ -2405,25 +2403,22 @@ __kernel void gemm_mm_native(IMAGE_DECLARATION(lhs),
#endif // defined(M0) && defined(N0) && defined(K0) && defined(K) && defined(DATA_TYPE)
#if defined(COLS_B) && defined(MULT_TRANSPOSE1XW_WIDTH) && defined(MULT_INTERLEAVE4X4_HEIGHT)
-/** This OpenCL kernel is optimised for Midgard. It computes the matrix multiplication between matrix A (src0) and matrix B (src1)
- * Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_32bit and @ref gemm_transpose1x4 before running the matrix multiplication
- *
- * Moreover, it can add a vector (src2) if the ADD_VEC_C parameter is passed at compile time.
+/** This OpenCL kernel is optimised for Midgard. It computes the matrix multiplication between matrix A reshaped (src0) and matrix B reshaped (src1)
*
* @note The number of columns of matrix B and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
- * @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (i.e. -DMULT_TRANSPOSE1XW_WIDTH=2)
- * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (i.e. -DMULT_INTERLEAVE4X4_HEIGHT=2)
- * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
- * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
+ * @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (e.g. -DMULT_TRANSPOSE1XW_WIDTH=2)
+ * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (e.g. -DMULT_INTERLEAVE4X4_HEIGHT=2)
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (e.g. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (e.g. a = [K, M, 16, Batches], b = [N, K, 16])
*
- * @note In case the output has to be reinterpreted as a 3D tensor (i.e. output of convolution layer), the following information must be passed at compile time:
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * The activation function is performed after the bias addition
+ * @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time:
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns matrix A NOT reshaped
*
- * @note In case a 3rd input (src2) needs to be added, the ADD_VEC_C parameter has to be passed at compile time as -DADD_VEC_C
- *
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
@@ -2436,10 +2431,12 @@ __kernel void gemm_mm_native(IMAGE_DECLARATION(lhs),
* @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes)
* @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix
- * @param[in] src2_ptr (Optional) Pointer to the source matrix. Supported data types: same as @p src0_ptr
- * @param[in] src2_stride_x (Optional) Stride of the source vector in X dimension (in bytes)
- * @param[in] src2_step_x (Optional) src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the source matrix
+ * @param[in] src2_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
+ * @param[in] src2_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
+ * @param[in] src2_step_x (Optional) src2_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src2_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
+ * @param[in] src2_step_y (Optional) src2_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src0_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
@@ -2448,17 +2445,21 @@ __kernel void gemm_mm_native(IMAGE_DECLARATION(lhs),
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] src0_stride_z Stride of the source matrix in Z dimension (in bytes)
* @param[in] src1_stride_z Stride of the source matrix in Z dimension (in bytes)
+ * @param[in] src2_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
*/
__kernel void gemm_mm_interleaved_transposed_f32(IMAGE_DECLARATION(src0),
IMAGE_DECLARATION(src1),
-#if defined(ADD_VEC_C)
- VECTOR_DECLARATION(src2),
-#endif /* defined(ADD_VEC_C) */
+#if defined(BETA)
+ IMAGE_DECLARATION(src2),
+#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint src0_stride_z,
uint src1_stride_z,
+#if defined(BETA)
+ uint src2_stride_z,
+#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
@@ -2496,10 +2497,10 @@ __kernel void gemm_mm_interleaved_transposed_f32(IMAGE_DECLARATION(src0),
src_addr_b += offset_row_b;
// Reset accumulators
- float4 c00 = 0.0f;
- float4 c10 = 0.0f;
- float4 c20 = 0.0f;
- float4 c30 = 0.0f;
+ float4 c0 = 0.0f;
+ float4 c1 = 0.0f;
+ float4 c2 = 0.0f;
+ float4 c3 = 0.0f;
for(; src_addr_b <= (src_end_addr_b - (int)(8 * MULT_TRANSPOSE1XW_WIDTH)); src_addr_a += 8 * MULT_INTERLEAVE4X4_HEIGHT, src_addr_b += 8 * MULT_TRANSPOSE1XW_WIDTH)
{
@@ -2507,19 +2508,19 @@ __kernel void gemm_mm_interleaved_transposed_f32(IMAGE_DECLARATION(src0),
float4 a0 = vload4(0, src_addr_a);
float4 b0 = vload4(0, src_addr_b);
- c00 += (float4)a0.s0 * b0;
- c10 += (float4)a0.s1 * b0;
- c20 += (float4)a0.s2 * b0;
- c30 += (float4)a0.s3 * b0;
+ c0 += (float4)a0.s0 * b0;
+ c1 += (float4)a0.s1 * b0;
+ c2 += (float4)a0.s2 * b0;
+ c3 += (float4)a0.s3 * b0;
// Load values from matrix A (interleaved) and matrix B (transposed)
a0 = vload4(0, src_addr_a + 4 * MULT_INTERLEAVE4X4_HEIGHT);
b0 = vload4(0, src_addr_b + 4 * MULT_TRANSPOSE1XW_WIDTH);
- c00 += (float4)a0.s0 * b0;
- c10 += (float4)a0.s1 * b0;
- c20 += (float4)a0.s2 * b0;
- c30 += (float4)a0.s3 * b0;
+ c0 += (float4)a0.s0 * b0;
+ c1 += (float4)a0.s1 * b0;
+ c2 += (float4)a0.s2 * b0;
+ c3 += (float4)a0.s3 * b0;
}
for(; src_addr_b < src_end_addr_b; src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT, src_addr_b += 4 * MULT_TRANSPOSE1XW_WIDTH)
@@ -2528,36 +2529,20 @@ __kernel void gemm_mm_interleaved_transposed_f32(IMAGE_DECLARATION(src0),
float4 a0 = vload4(0, src_addr_a);
float4 b0 = vload4(0, src_addr_b);
- c00 += (float4)a0.s0 * b0;
- c10 += (float4)a0.s1 * b0;
- c20 += (float4)a0.s2 * b0;
- c30 += (float4)a0.s3 * b0;
+ c0 += (float4)a0.s0 * b0;
+ c1 += (float4)a0.s1 * b0;
+ c2 += (float4)a0.s2 * b0;
+ c3 += (float4)a0.s3 * b0;
}
// Compute destination address
Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
-#if defined(ALPHA)
- // Multiply by the weight of matrix product
- c00 = c00 * (float4)ALPHA;
- c10 = c10 * (float4)ALPHA;
- c20 = c20 * (float4)ALPHA;
- c30 = c30 * (float4)ALPHA;
-#endif // defined(ALPHA)
-
-#if defined(ADD_VEC_C)
- __global float *src2_addr = (__global float *)(src2_ptr + src2_offset_first_element_in_bytes + get_global_id(0) * src2_step_x);
- float4 c0 = vload4(0, src2_addr);
-
- c00 += c0;
- c10 += c0;
- c20 += c0;
- c30 += c0;
-#endif /* defined(ADD_VEC_C) */
-
// Compute dst address
__global uchar *dst_addr = offset(&dst, 0, 0);
+ uint4 zout = 0;
+
#if defined(REINTERPRET_OUTPUT_AS_3D)
// Since we store a 2D output tile in a 3D tensor, we need to check when the plane changes across the z dimension
// in order to take into account the presence of possible cross plane paddings
@@ -2575,8 +2560,8 @@ __kernel void gemm_mm_interleaved_transposed_f32(IMAGE_DECLARATION(src0),
// |__________________|
// The plane (zout) is calculated dividing M (get_global_id(1) * 4) by HEIGHT_GEMM3D
- uint4 zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * 4)) / (uint4)HEIGHT_GEMM3D;
- zout = min(DEPTH_GEMM3D - 1, zout);
+ zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * 4)) / (uint4)HEIGHT_GEMM3D;
+ zout = min(DEPTH_GEMM3D - 1, zout);
// Add offset due to the cross plane paddings
zout *= (cross_plane_pad * dst_stride_y);
@@ -2584,45 +2569,76 @@ __kernel void gemm_mm_interleaved_transposed_f32(IMAGE_DECLARATION(src0),
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
-
- // Store 4x4 block
- vstore4(c00, 0, (__global float *)(dst_addr + 0 * dst_stride_y + zout.s0));
- vstore4(c10, 0, (__global float *)(dst_addr + 1 * dst_stride_y + zout.s1));
- vstore4(c20, 0, (__global float *)(dst_addr + 2 * dst_stride_y + zout.s2));
- vstore4(c30, 0, (__global float *)(dst_addr + 3 * dst_stride_y + zout.s3));
-
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
+#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+
+ // Multiply by the weight of matrix-matrix product and store the result
+#if defined(ALPHA)
+ SCALE_BLOCK(4, float, c, ALPHA);
+#endif // defined(ALPHA)
+
+ // Add beta*bias
+#if defined(BETA)
+ REPEAT_VAR_INIT_TO_CONST(4, uint, zero, 0);
+
+#if defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)4 * sizeof(float));
+
+ LOAD_BLOCK(1, 4, float, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(1, float, bias, BETA);
+#endif // UNIT_BIAS
+
+ // c = c + bias[broadcasted]
+ ADD_BLOCK_BROADCAST(4, c, bias0);
+
+#else // defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)4 * sizeof(float)) + (get_global_id(1) * (uint)4 * src2_stride_y) + get_global_id(
+ 2) * src2_stride_z;
+
+ LOAD_BLOCK(4, 4, float, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(4, float, bias, BETA);
+#endif // UNIT_BIAS
+
+ // c = c + bias
+ ADD_BLOCK(4, c, bias);
+
+#endif // defined(BROADCAST_BIAS)
+#endif // defined(BETA)
+
+#if defined(ACTIVATION_TYPE)
+ ACTIVATION_BLOCK(4, ACTIVATION_TYPE, float, c, A_VAL, B_VAL);
+#endif // defined(ACTIVATION_TYPE)
// Store 4x4 block
- vstore4(c00, 0, (__global float *)(dst_addr + 0 * dst_stride_y));
- vstore4(c10, 0, (__global float *)(dst_addr + 1 * dst_stride_y));
- vstore4(c20, 0, (__global float *)(dst_addr + 2 * dst_stride_y));
- vstore4(c30, 0, (__global float *)(dst_addr + 3 * dst_stride_y));
-#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+ vstore4(c0, 0, (__global float *)(dst_addr + 0 * dst_stride_y + zout.s0));
+ vstore4(c1, 0, (__global float *)(dst_addr + 1 * dst_stride_y + zout.s1));
+ vstore4(c2, 0, (__global float *)(dst_addr + 2 * dst_stride_y + zout.s2));
+ vstore4(c3, 0, (__global float *)(dst_addr + 3 * dst_stride_y + zout.s3));
}
-/** This OpenCL kernel is optimized for Bifrost. It computes the matrix multiplication between matrix A (src0) and matrix B (src1)
- * Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_32bit and @ref gemm_transpose1x4 before running the matrix multiplication.
- *
- * Moreover, it can add a vector (src2) if the ADD_VEC_C parameter is passed at compile time.
+/** This OpenCL kernel is optimized for Bifrost and tt computes the matrix multiplication between matrix A reshaped (src0) and matrix B reshaped (src1)
*
* @note The number of columns of matrix B and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
- * @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (i.e. -DMULT_TRANSPOSE1XW_WIDTH=2)
- * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (i.e. -DMULT_INTERLEAVE4X4_HEIGHT=2)
- * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (i.e. -DMULT_INTERLEAVE4X4_HEIGHT=2)
- * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
- * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
+ * @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (e.g. -DMULT_TRANSPOSE1XW_WIDTH=2)
+ * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (e.g. -DMULT_INTERLEAVE4X4_HEIGHT=2)
+ * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (e.g. -DMULT_INTERLEAVE4X4_HEIGHT=2)
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (e.g. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (e.g. a = [K, M, 16, Batches], b = [N, K, 16])
*
- * @note In case the output has to be reinterpreted as a 3D tensor (i.e. output of convolution layer), the following information must be passed at compile time:
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * The activation function is performed after the bias addition
+ * @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time:
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns matrix A NOT reshaped
*
- * @note In case a 3rd input (src2) needs to be added, the ADD_VEC_C parameter has to be passed at compile time as -DADD_VEC_C
- *
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
@@ -2635,10 +2651,12 @@ __kernel void gemm_mm_interleaved_transposed_f32(IMAGE_DECLARATION(src0),
* @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes)
* @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix
- * @param[in] src2_ptr (Optional) Pointer to the source matrix. Supported data types: same as @p src0_ptr
- * @param[in] src2_stride_x (Optional) Stride of the source vector in X dimension (in bytes)
- * @param[in] src2_step_x (Optional) src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the source matrix
+ * @param[in] src2_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
+ * @param[in] src2_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
+ * @param[in] src2_step_x (Optional) src2_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src2_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
+ * @param[in] src2_step_y (Optional) src2_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src0_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
@@ -2647,17 +2665,21 @@ __kernel void gemm_mm_interleaved_transposed_f32(IMAGE_DECLARATION(src0),
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] src0_stride_z Stride of the source matrix in Z dimension (in bytes)
* @param[in] src1_stride_z Stride of the source matrix in Z dimension (in bytes)
+ * @param[in] src2_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
*/
__kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0),
IMAGE_DECLARATION(src1),
-#if defined(ADD_VEC_C)
- VECTOR_DECLARATION(src2),
-#endif /* defined(ADD_VEC_C) */
+#if defined(BETA)
+ IMAGE_DECLARATION(src2),
+#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint src0_stride_z,
uint src1_stride_z,
+#if defined(BETA)
+ uint src2_stride_z,
+#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
@@ -2692,22 +2714,10 @@ __kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0)
src_addr_b += offset_row_b;
// Reset accumulators
- float c00 = 0.0f;
- float c01 = 0.0f;
- float c02 = 0.0f;
- float c03 = 0.0f;
- float c10 = 0.0f;
- float c11 = 0.0f;
- float c12 = 0.0f;
- float c13 = 0.0f;
- float c20 = 0.0f;
- float c21 = 0.0f;
- float c22 = 0.0f;
- float c23 = 0.0f;
- float c30 = 0.0f;
- float c31 = 0.0f;
- float c32 = 0.0f;
- float c33 = 0.0f;
+ float4 c0 = 0.0f;
+ float4 c1 = 0.0f;
+ float4 c2 = 0.0f;
+ float4 c3 = 0.0f;
#define COLS_MTX_B (COLS_B / (4 * MULT_TRANSPOSE1XW_WIDTH))
@@ -2721,25 +2731,25 @@ __kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0)
src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT;
src_addr_b += 4 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma(a0.s0, b0.s0, c00);
- c01 = fma(a0.s0, b0.s1, c01);
- c02 = fma(a0.s0, b0.s2, c02);
- c03 = fma(a0.s0, b0.s3, c03);
+ c0.s0 = fma(a0.s0, b0.s0, c0.s0);
+ c0.s1 = fma(a0.s0, b0.s1, c0.s1);
+ c0.s2 = fma(a0.s0, b0.s2, c0.s2);
+ c0.s3 = fma(a0.s0, b0.s3, c0.s3);
- c10 = fma(a0.s1, b0.s0, c10);
- c11 = fma(a0.s1, b0.s1, c11);
- c12 = fma(a0.s1, b0.s2, c12);
- c13 = fma(a0.s1, b0.s3, c13);
+ c1.s0 = fma(a0.s1, b0.s0, c1.s0);
+ c1.s1 = fma(a0.s1, b0.s1, c1.s1);
+ c1.s2 = fma(a0.s1, b0.s2, c1.s2);
+ c1.s3 = fma(a0.s1, b0.s3, c1.s3);
- c20 = fma(a0.s2, b0.s0, c20);
- c21 = fma(a0.s2, b0.s1, c21);
- c22 = fma(a0.s2, b0.s2, c22);
- c23 = fma(a0.s2, b0.s3, c23);
+ c2.s0 = fma(a0.s2, b0.s0, c2.s0);
+ c2.s1 = fma(a0.s2, b0.s1, c2.s1);
+ c2.s2 = fma(a0.s2, b0.s2, c2.s2);
+ c2.s3 = fma(a0.s2, b0.s3, c2.s3);
- c30 = fma(a0.s3, b0.s0, c30);
- c31 = fma(a0.s3, b0.s1, c31);
- c32 = fma(a0.s3, b0.s2, c32);
- c33 = fma(a0.s3, b0.s3, c33);
+ c3.s0 = fma(a0.s3, b0.s0, c3.s0);
+ c3.s1 = fma(a0.s3, b0.s1, c3.s1);
+ c3.s2 = fma(a0.s3, b0.s2, c3.s2);
+ c3.s3 = fma(a0.s3, b0.s3, c3.s3);
// Load values from matrix A (interleaved) and matrix B (transposed)
a0 = vload4(0, src_addr_a);
@@ -2748,25 +2758,25 @@ __kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0)
src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT;
src_addr_b += 4 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma(a0.s0, b0.s0, c00);
- c01 = fma(a0.s0, b0.s1, c01);
- c02 = fma(a0.s0, b0.s2, c02);
- c03 = fma(a0.s0, b0.s3, c03);
+ c0.s0 = fma(a0.s0, b0.s0, c0.s0);
+ c0.s1 = fma(a0.s0, b0.s1, c0.s1);
+ c0.s2 = fma(a0.s0, b0.s2, c0.s2);
+ c0.s3 = fma(a0.s0, b0.s3, c0.s3);
- c10 = fma(a0.s1, b0.s0, c10);
- c11 = fma(a0.s1, b0.s1, c11);
- c12 = fma(a0.s1, b0.s2, c12);
- c13 = fma(a0.s1, b0.s3, c13);
+ c1.s0 = fma(a0.s1, b0.s0, c1.s0);
+ c1.s1 = fma(a0.s1, b0.s1, c1.s1);
+ c1.s2 = fma(a0.s1, b0.s2, c1.s2);
+ c1.s3 = fma(a0.s1, b0.s3, c1.s3);
- c20 = fma(a0.s2, b0.s0, c20);
- c21 = fma(a0.s2, b0.s1, c21);
- c22 = fma(a0.s2, b0.s2, c22);
- c23 = fma(a0.s2, b0.s3, c23);
+ c2.s0 = fma(a0.s2, b0.s0, c2.s0);
+ c2.s1 = fma(a0.s2, b0.s1, c2.s1);
+ c2.s2 = fma(a0.s2, b0.s2, c2.s2);
+ c2.s3 = fma(a0.s2, b0.s3, c2.s3);
- c30 = fma(a0.s3, b0.s0, c30);
- c31 = fma(a0.s3, b0.s1, c31);
- c32 = fma(a0.s3, b0.s2, c32);
- c33 = fma(a0.s3, b0.s3, c33);
+ c3.s0 = fma(a0.s3, b0.s0, c3.s0);
+ c3.s1 = fma(a0.s3, b0.s1, c3.s1);
+ c3.s2 = fma(a0.s3, b0.s2, c3.s2);
+ c3.s3 = fma(a0.s3, b0.s3, c3.s3);
// Load values from matrix A (interleaved) and matrix B (transposed)
a0 = vload4(0, src_addr_a);
@@ -2775,25 +2785,25 @@ __kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0)
src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT;
src_addr_b += 4 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma(a0.s0, b0.s0, c00);
- c01 = fma(a0.s0, b0.s1, c01);
- c02 = fma(a0.s0, b0.s2, c02);
- c03 = fma(a0.s0, b0.s3, c03);
+ c0.s0 = fma(a0.s0, b0.s0, c0.s0);
+ c0.s1 = fma(a0.s0, b0.s1, c0.s1);
+ c0.s2 = fma(a0.s0, b0.s2, c0.s2);
+ c0.s3 = fma(a0.s0, b0.s3, c0.s3);
- c10 = fma(a0.s1, b0.s0, c10);
- c11 = fma(a0.s1, b0.s1, c11);
- c12 = fma(a0.s1, b0.s2, c12);
- c13 = fma(a0.s1, b0.s3, c13);
+ c1.s0 = fma(a0.s1, b0.s0, c1.s0);
+ c1.s1 = fma(a0.s1, b0.s1, c1.s1);
+ c1.s2 = fma(a0.s1, b0.s2, c1.s2);
+ c1.s3 = fma(a0.s1, b0.s3, c1.s3);
- c20 = fma(a0.s2, b0.s0, c20);
- c21 = fma(a0.s2, b0.s1, c21);
- c22 = fma(a0.s2, b0.s2, c22);
- c23 = fma(a0.s2, b0.s3, c23);
+ c2.s0 = fma(a0.s2, b0.s0, c2.s0);
+ c2.s1 = fma(a0.s2, b0.s1, c2.s1);
+ c2.s2 = fma(a0.s2, b0.s2, c2.s2);
+ c2.s3 = fma(a0.s2, b0.s3, c2.s3);
- c30 = fma(a0.s3, b0.s0, c30);
- c31 = fma(a0.s3, b0.s1, c31);
- c32 = fma(a0.s3, b0.s2, c32);
- c33 = fma(a0.s3, b0.s3, c33);
+ c3.s0 = fma(a0.s3, b0.s0, c3.s0);
+ c3.s1 = fma(a0.s3, b0.s1, c3.s1);
+ c3.s2 = fma(a0.s3, b0.s2, c3.s2);
+ c3.s3 = fma(a0.s3, b0.s3, c3.s3);
// Load values from matrix A (interleaved) and matrix B (transposed)
a0 = vload4(0, src_addr_a);
@@ -2802,25 +2812,25 @@ __kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0)
src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT;
src_addr_b += 4 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma(a0.s0, b0.s0, c00);
- c01 = fma(a0.s0, b0.s1, c01);
- c02 = fma(a0.s0, b0.s2, c02);
- c03 = fma(a0.s0, b0.s3, c03);
-
- c10 = fma(a0.s1, b0.s0, c10);
- c11 = fma(a0.s1, b0.s1, c11);
- c12 = fma(a0.s1, b0.s2, c12);
- c13 = fma(a0.s1, b0.s3, c13);
-
- c20 = fma(a0.s2, b0.s0, c20);
- c21 = fma(a0.s2, b0.s1, c21);
- c22 = fma(a0.s2, b0.s2, c22);
- c23 = fma(a0.s2, b0.s3, c23);
-
- c30 = fma(a0.s3, b0.s0, c30);
- c31 = fma(a0.s3, b0.s1, c31);
- c32 = fma(a0.s3, b0.s2, c32);
- c33 = fma(a0.s3, b0.s3, c33);
+ c0.s0 = fma(a0.s0, b0.s0, c0.s0);
+ c0.s1 = fma(a0.s0, b0.s1, c0.s1);
+ c0.s2 = fma(a0.s0, b0.s2, c0.s2);
+ c0.s3 = fma(a0.s0, b0.s3, c0.s3);
+
+ c1.s0 = fma(a0.s1, b0.s0, c1.s0);
+ c1.s1 = fma(a0.s1, b0.s1, c1.s1);
+ c1.s2 = fma(a0.s1, b0.s2, c1.s2);
+ c1.s3 = fma(a0.s1, b0.s3, c1.s3);
+
+ c2.s0 = fma(a0.s2, b0.s0, c2.s0);
+ c2.s1 = fma(a0.s2, b0.s1, c2.s1);
+ c2.s2 = fma(a0.s2, b0.s2, c2.s2);
+ c2.s3 = fma(a0.s2, b0.s3, c2.s3);
+
+ c3.s0 = fma(a0.s3, b0.s0, c3.s0);
+ c3.s1 = fma(a0.s3, b0.s1, c3.s1);
+ c3.s2 = fma(a0.s3, b0.s2, c3.s2);
+ c3.s3 = fma(a0.s3, b0.s3, c3.s3);
}
for(; i < (int)(COLS_MTX_B); ++i)
@@ -2832,74 +2842,34 @@ __kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0)
src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT;
src_addr_b += 4 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma(a0.s0, b0.s0, c00);
- c01 = fma(a0.s0, b0.s1, c01);
- c02 = fma(a0.s0, b0.s2, c02);
- c03 = fma(a0.s0, b0.s3, c03);
-
- c10 = fma(a0.s1, b0.s0, c10);
- c11 = fma(a0.s1, b0.s1, c11);
- c12 = fma(a0.s1, b0.s2, c12);
- c13 = fma(a0.s1, b0.s3, c13);
-
- c20 = fma(a0.s2, b0.s0, c20);
- c21 = fma(a0.s2, b0.s1, c21);
- c22 = fma(a0.s2, b0.s2, c22);
- c23 = fma(a0.s2, b0.s3, c23);
-
- c30 = fma(a0.s3, b0.s0, c30);
- c31 = fma(a0.s3, b0.s1, c31);
- c32 = fma(a0.s3, b0.s2, c32);
- c33 = fma(a0.s3, b0.s3, c33);
+ c0.s0 = fma(a0.s0, b0.s0, c0.s0);
+ c0.s1 = fma(a0.s0, b0.s1, c0.s1);
+ c0.s2 = fma(a0.s0, b0.s2, c0.s2);
+ c0.s3 = fma(a0.s0, b0.s3, c0.s3);
+
+ c1.s0 = fma(a0.s1, b0.s0, c1.s0);
+ c1.s1 = fma(a0.s1, b0.s1, c1.s1);
+ c1.s2 = fma(a0.s1, b0.s2, c1.s2);
+ c1.s3 = fma(a0.s1, b0.s3, c1.s3);
+
+ c2.s0 = fma(a0.s2, b0.s0, c2.s0);
+ c2.s1 = fma(a0.s2, b0.s1, c2.s1);
+ c2.s2 = fma(a0.s2, b0.s2, c2.s2);
+ c2.s3 = fma(a0.s2, b0.s3, c2.s3);
+
+ c3.s0 = fma(a0.s3, b0.s0, c3.s0);
+ c3.s1 = fma(a0.s3, b0.s1, c3.s1);
+ c3.s2 = fma(a0.s3, b0.s2, c3.s2);
+ c3.s3 = fma(a0.s3, b0.s3, c3.s3);
}
// Compute destination address
Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
-#if defined(ALPHA)
- // Multiply by the weight of matrix product
- c00 = c00 * ALPHA;
- c01 = c01 * ALPHA;
- c02 = c02 * ALPHA;
- c03 = c03 * ALPHA;
- c10 = c10 * ALPHA;
- c11 = c11 * ALPHA;
- c12 = c12 * ALPHA;
- c13 = c13 * ALPHA;
- c20 = c20 * ALPHA;
- c21 = c21 * ALPHA;
- c22 = c22 * ALPHA;
- c23 = c23 * ALPHA;
- c30 = c30 * ALPHA;
- c31 = c31 * ALPHA;
- c32 = c32 * ALPHA;
- c33 = c33 * ALPHA;
-#endif // defined(ALPHA)
-
// Compute dst address
__global uchar *dst_addr = offset(&dst, 0, 0);
-#if defined(ADD_VEC_C)
- __global float *src2_addr = (__global float *)(src2_ptr + src2_offset_first_element_in_bytes + get_global_id(0) * src2_step_x);
- float4 c0 = vload4(0, src2_addr);
-
- c00 += c0.s0;
- c01 += c0.s1;
- c02 += c0.s2;
- c03 += c0.s3;
- c10 += c0.s0;
- c11 += c0.s1;
- c12 += c0.s2;
- c13 += c0.s3;
- c20 += c0.s0;
- c21 += c0.s1;
- c22 += c0.s2;
- c23 += c0.s3;
- c30 += c0.s0;
- c31 += c0.s1;
- c32 += c0.s2;
- c33 += c0.s3;
-#endif /* defined(ADD_VEC_C) */
+ uint4 zout = 0;
#if defined(REINTERPRET_OUTPUT_AS_3D)
// Since we store a 2D output tile in a 3D tensor, we need to check when the plane changes across the z dimension
@@ -2918,8 +2888,8 @@ __kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0)
// |__________________|
// The plane (zout) is calculated dividing M (get_global_id(1) * 4) by HEIGHT_GEMM3D
- uint4 zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * 4)) / (uint4)HEIGHT_GEMM3D;
- zout = min(DEPTH_GEMM3D - 1, zout);
+ zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * 4)) / (uint4)HEIGHT_GEMM3D;
+ zout = min(DEPTH_GEMM3D - 1, zout);
// Add offset due to the cross plane paddings
zout *= (cross_plane_pad * dst_stride_y);
@@ -2927,48 +2897,79 @@ __kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0)
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
-
- // Store 4x4 block
- vstore4((float4)(c00, c01, c02, c03), 0, (__global float *)(dst_addr + 0 * dst_stride_y + zout.s0));
- vstore4((float4)(c10, c11, c12, c13), 0, (__global float *)(dst_addr + 1 * dst_stride_y + zout.s1));
- vstore4((float4)(c20, c21, c22, c23), 0, (__global float *)(dst_addr + 2 * dst_stride_y + zout.s2));
- vstore4((float4)(c30, c31, c32, c33), 0, (__global float *)(dst_addr + 3 * dst_stride_y + zout.s3));
-
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
+#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+
+ // Multiply by the weight of matrix-matrix product and store the result
+#if defined(ALPHA)
+ SCALE_BLOCK(4, float, c, ALPHA);
+#endif // defined(ALPHA)
+
+ // Add beta*bias
+#if defined(BETA)
+ REPEAT_VAR_INIT_TO_CONST(4, uint, zero, 0);
+
+#if defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)4 * sizeof(float));
+
+ LOAD_BLOCK(1, 4, float, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(1, float, bias, BETA);
+#endif // UNIT_BIAS
+
+ // c = c + bias[broadcasted]
+ ADD_BLOCK_BROADCAST(4, c, bias0);
+
+#else // defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)4 * sizeof(float)) + (get_global_id(1) * (uint)4 * src2_stride_y) + get_global_id(
+ 2) * src2_stride_z;
+
+ LOAD_BLOCK(4, 4, float, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(4, float, bias, BETA);
+#endif // UNIT_BIAS
+
+ // c = c + bias
+ ADD_BLOCK(4, c, bias);
+
+#endif // defined(BROADCAST_BIAS)
+#endif // defined(BETA)
+
+#if defined(ACTIVATION_TYPE)
+ ACTIVATION_BLOCK(4, ACTIVATION_TYPE, float, c, A_VAL, B_VAL);
+#endif // defined(ACTIVATION_TYPE)
// Store 4x4 block
- vstore4((float4)(c00, c01, c02, c03), 0, (__global float *)(dst_addr + 0 * dst_stride_y));
- vstore4((float4)(c10, c11, c12, c13), 0, (__global float *)(dst_addr + 1 * dst_stride_y));
- vstore4((float4)(c20, c21, c22, c23), 0, (__global float *)(dst_addr + 2 * dst_stride_y));
- vstore4((float4)(c30, c31, c32, c33), 0, (__global float *)(dst_addr + 3 * dst_stride_y));
-#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+ vstore4(c0, 0, (__global float *)(dst_addr + 0 * dst_stride_y + zout.s0));
+ vstore4(c1, 0, (__global float *)(dst_addr + 1 * dst_stride_y + zout.s1));
+ vstore4(c2, 0, (__global float *)(dst_addr + 2 * dst_stride_y + zout.s2));
+ vstore4(c3, 0, (__global float *)(dst_addr + 3 * dst_stride_y + zout.s3));
}
// Undefine local defines
#undef COLS_MTX_B
#if defined(ARM_COMPUTE_OPENCL_FP16_ENABLED)
-/** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1)
- * Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_16bit and @ref gemm_transpose1x8 before running the matrix multiplication
- *
- * Moreover, it can add a vector (src2) if the ADD_VEC_C parameter is passed at compile time.
+/** This OpenCL kernel computes the matrix multiplication between matrix A reshaped (src0) and matrix B reshaped (src1)
*
* @note The number of columns of matrix B and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
- * @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (i.e. -DMULT_TRANSPOSE1XW_WIDTH=2)
- * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (i.e. -DMULT_INTERLEAVE4X4_HEIGHT=2)
- * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
- * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
+ * @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (e.g. -DMULT_TRANSPOSE1XW_WIDTH=2)
+ * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (e.g. -DMULT_INTERLEAVE4X4_HEIGHT=2)
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (e.g. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (e.g. a = [K, M, 16, Batches], b = [N, K, 16])
*
- * @note In case the output has to be reinterpreted as a 3D tensor (i.e. output of convolution layer), the following information must be passed at compile time:
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * The activation function is performed after the bias addition
+ * @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time:
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns matrix A NOT reshaped
*
- * @note In case a 3rd input (src2) needs to be added, the ADD_VEC_C parameter has to be passed at compile time as -DADD_VEC_C
- *
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
@@ -2981,10 +2982,12 @@ __kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0)
* @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes)
* @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix
- * @param[in] src2_ptr (Optional) Pointer to the source matrix. Supported data types: same as @p src0_ptr
- * @param[in] src2_stride_x (Optional) Stride of the source vector in X dimension (in bytes)
- * @param[in] src2_step_x (Optional) src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the source matrix
+ * @param[in] src2_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
+ * @param[in] src2_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
+ * @param[in] src2_step_x (Optional) src2_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src2_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
+ * @param[in] src2_step_y (Optional) src2_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src0_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
@@ -2993,17 +2996,21 @@ __kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] src0_stride_z Stride of the source matrix in Z dimension (in bytes)
* @param[in] src1_stride_z Stride of the source matrix in Z dimension (in bytes)
+ * @param[in] src2_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
*/
__kernel void gemm_mm_interleaved_transposed_f16(IMAGE_DECLARATION(src0),
IMAGE_DECLARATION(src1),
-#if defined(ADD_VEC_C)
- VECTOR_DECLARATION(src2),
-#endif /* defined(ADD_VEC_C) */
+#if defined(BETA)
+ IMAGE_DECLARATION(src2),
+#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint src0_stride_z,
uint src1_stride_z,
+#if defined(BETA)
+ uint src2_stride_z,
+#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
@@ -3041,10 +3048,10 @@ __kernel void gemm_mm_interleaved_transposed_f16(IMAGE_DECLARATION(src0),
src_addr_b += offset_row_b;
// Reset accumulators
- half8 c00 = 0.0f;
- half8 c10 = 0.0f;
- half8 c20 = 0.0f;
- half8 c30 = 0.0f;
+ half8 c0 = 0.0f;
+ half8 c1 = 0.0f;
+ half8 c2 = 0.0f;
+ half8 c3 = 0.0f;
for(; src_addr_b <= (src_end_addr_b - (int)(16 * MULT_TRANSPOSE1XW_WIDTH)); src_addr_a += 8 * MULT_INTERLEAVE4X4_HEIGHT, src_addr_b += 16 * MULT_TRANSPOSE1XW_WIDTH)
{
@@ -3052,19 +3059,19 @@ __kernel void gemm_mm_interleaved_transposed_f16(IMAGE_DECLARATION(src0),
half4 a0 = vload4(0, src_addr_a);
half8 b0 = vload8(0, src_addr_b);
- c00 += (half8)a0.s0 * b0;
- c10 += (half8)a0.s1 * b0;
- c20 += (half8)a0.s2 * b0;
- c30 += (half8)a0.s3 * b0;
+ c0 += (half8)a0.s0 * b0;
+ c1 += (half8)a0.s1 * b0;
+ c2 += (half8)a0.s2 * b0;
+ c3 += (half8)a0.s3 * b0;
// Load values from matrix A (interleaved) and matrix B (transposed)
a0 = vload4(0, src_addr_a + 4 * MULT_INTERLEAVE4X4_HEIGHT);
b0 = vload8(0, src_addr_b + 8 * MULT_TRANSPOSE1XW_WIDTH);
- c00 += (half8)a0.s0 * b0;
- c10 += (half8)a0.s1 * b0;
- c20 += (half8)a0.s2 * b0;
- c30 += (half8)a0.s3 * b0;
+ c0 += (half8)a0.s0 * b0;
+ c1 += (half8)a0.s1 * b0;
+ c2 += (half8)a0.s2 * b0;
+ c3 += (half8)a0.s3 * b0;
}
for(; src_addr_b < src_end_addr_b; src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT, src_addr_b += 8 * MULT_TRANSPOSE1XW_WIDTH)
@@ -3073,40 +3080,20 @@ __kernel void gemm_mm_interleaved_transposed_f16(IMAGE_DECLARATION(src0),
half4 a0 = vload4(0, src_addr_a);
half8 b0 = vload8(0, src_addr_b);
- c00 += (half8)a0.s0 * b0;
- c10 += (half8)a0.s1 * b0;
- c20 += (half8)a0.s2 * b0;
- c30 += (half8)a0.s3 * b0;
+ c0 += (half8)a0.s0 * b0;
+ c1 += (half8)a0.s1 * b0;
+ c2 += (half8)a0.s2 * b0;
+ c3 += (half8)a0.s3 * b0;
}
// Compute destination address
Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
-#if defined(ALPHA)
- // Multiply by the weight of matrix product
- c00 = c00 * (half8)ALPHA;
- c10 = c10 * (half8)ALPHA;
- c20 = c20 * (half8)ALPHA;
- c30 = c30 * (half8)ALPHA;
-#endif // defined(ALPHA)
-
-#if defined(ADD_VEC_C)
- // *INDENT-OFF*
- // clang-format off
- __global half *src2_addr = (__global half *)(src2_ptr + src2_offset_first_element_in_bytes + get_global_id(0) * src2_step_x);
- half8 c0 = vload8(0, src2_addr);
- // clang-format on
- // *INDENT-ON*
-
- c00 += c0;
- c10 += c0;
- c20 += c0;
- c30 += c0;
-#endif /* defined(ADD_VEC_C) */
-
// Compute dst address
__global uchar *dst_addr = offset(&dst, 0, 0);
+ uint4 zout = 0;
+
#if defined(REINTERPRET_OUTPUT_AS_3D)
// Since we store a 2D output tile in a 3D tensor, we need to check when the plane changes across the z dimension
// in order to take into account the presence of possible cross plane paddings
@@ -3124,8 +3111,8 @@ __kernel void gemm_mm_interleaved_transposed_f16(IMAGE_DECLARATION(src0),
// |__________________|
// The plane (zout) is calculated dividing M (get_global_id(1) * 4) by HEIGHT_GEMM3D
- uint4 zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * 4)) / (uint4)HEIGHT_GEMM3D;
- zout = min(DEPTH_GEMM3D - 1, zout);
+ zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * 4)) / (uint4)HEIGHT_GEMM3D;
+ zout = min(DEPTH_GEMM3D - 1, zout);
// Add offset due to the cross plane paddings
zout *= (cross_plane_pad * dst_stride_y);
@@ -3133,44 +3120,76 @@ __kernel void gemm_mm_interleaved_transposed_f16(IMAGE_DECLARATION(src0),
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
-
- // Store 4x8 block
- vstore8(c00, 0, (__global half *)(dst_addr + 0 * dst_stride_y + zout.s0));
- vstore8(c10, 0, (__global half *)(dst_addr + 1 * dst_stride_y + zout.s1));
- vstore8(c20, 0, (__global half *)(dst_addr + 2 * dst_stride_y + zout.s2));
- vstore8(c30, 0, (__global half *)(dst_addr + 3 * dst_stride_y + zout.s3));
-
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
+#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+
+ // Multiply by the weight of matrix-matrix product and store the result
+#if defined(ALPHA)
+ SCALE_BLOCK(4, half, c, ALPHA);
+#endif // defined(ALPHA)
+
+ // Add beta*bias
+#if defined(BETA)
+ REPEAT_VAR_INIT_TO_CONST(4, uint, zero, 0);
+
+#if defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)8 * sizeof(half));
+
+ LOAD_BLOCK(1, 8, half, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(1, half, bias, BETA);
+#endif // UNIT_BIAS
+
+ // c = c + bias[broadcasted]
+ ADD_BLOCK_BROADCAST(4, c, bias0);
+
+#else // defined(BROADCAST_BIAS)
+
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)8 * sizeof(half)) + (get_global_id(1) * (uint)4 * src2_stride_y) + get_global_id(
+ 2) * src2_stride_z;
+
+ LOAD_BLOCK(4, 8, half, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(4, half, bias, BETA);
+#endif // UNIT_BIAS
+
+ // c = c + bias
+ ADD_BLOCK(4, c, bias);
+
+#endif // defined(BROADCAST_BIAS)
+#endif // defined(BETA)
+
+#if defined(ACTIVATION_TYPE)
+ ACTIVATION_BLOCK(4, ACTIVATION_TYPE, half, c, A_VAL, B_VAL);
+#endif // defined(ACTIVATION_TYPE)
// Store 4x8 block
- vstore8(c00, 0, (__global half *)(dst_addr + 0 * dst_stride_y));
- vstore8(c10, 0, (__global half *)(dst_addr + 1 * dst_stride_y));
- vstore8(c20, 0, (__global half *)(dst_addr + 2 * dst_stride_y));
- vstore8(c30, 0, (__global half *)(dst_addr + 3 * dst_stride_y));
-#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+ vstore8(c0, 0, (__global half *)(dst_addr + 0 * dst_stride_y + zout.s0));
+ vstore8(c1, 0, (__global half *)(dst_addr + 1 * dst_stride_y + zout.s1));
+ vstore8(c2, 0, (__global half *)(dst_addr + 2 * dst_stride_y + zout.s2));
+ vstore8(c3, 0, (__global half *)(dst_addr + 3 * dst_stride_y + zout.s3));
}
-/** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1) while accumulating the result in a 32 floating point variable.
- * Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_16bit and @ref gemm_transpose1x8 before running the matrix multiplication
- *
- * Moreover, it can add a vector (src2) if the ADD_VEC_C parameter is passed at compile time.
+/** This OpenCL kernel computes the matrix multiplication between matrix A reshaped (src0) and matrix B reshaped (src1) while accumulating the result in a 32 floating point variable.
*
* @note The number of columns of matrix B and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
- * @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (i.e. -DMULT_TRANSPOSE1XW_WIDTH=2)
- * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (i.e. -DMULT_INTERLEAVE4X4_HEIGHT=2)
- * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
- * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
+ * @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (e.g. -DMULT_TRANSPOSE1XW_WIDTH=2)
+ * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (e.g. -DMULT_INTERLEAVE4X4_HEIGHT=2)
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (e.g. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (e.g. a = [K, M, 16, Batches], b = [N, K, 16])
*
- * @note In case the output has to be reinterpreted as a 3D tensor (i.e. output of convolution layer), the following information must be passed at compile time:
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * The activation function is performed after the bias addition
+ * @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time:
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns matrix A NOT reshaped
*
- * @note In case a 3rd input (src2) needs to be added, the ADD_VEC_C parameter has to be passed at compile time as -DADD_VEC_C
- *
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
@@ -3183,10 +3202,12 @@ __kernel void gemm_mm_interleaved_transposed_f16(IMAGE_DECLARATION(src0),
* @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes)
* @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix
- * @param[in] src2_ptr (Optional) Pointer to the source matrix. Supported data types: same as @p src0_ptr
- * @param[in] src2_stride_x (Optional) Stride of the source vector in X dimension (in bytes)
- * @param[in] src2_step_x (Optional) src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the source matrix
+ * @param[in] src2_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
+ * @param[in] src2_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
+ * @param[in] src2_step_x (Optional) src2_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src2_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
+ * @param[in] src2_step_y (Optional) src2_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src0_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
@@ -3195,17 +3216,21 @@ __kernel void gemm_mm_interleaved_transposed_f16(IMAGE_DECLARATION(src0),
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] src0_stride_z Stride of the source matrix in Z dimension (in bytes)
* @param[in] src1_stride_z Stride of the source matrix in Z dimension (in bytes)
+ * @param[in] src2_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
*/
__kernel void gemm_mm_interleaved_transposed_f16_acc32(IMAGE_DECLARATION(src0),
IMAGE_DECLARATION(src1),
-#if defined(ADD_VEC_C)
- VECTOR_DECLARATION(src2),
-#endif /* defined(ADD_VEC_C) */
+#if defined(BETA)
+ IMAGE_DECLARATION(src2),
+#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint src0_stride_z,
uint src1_stride_z,
+#if defined(BETA)
+ uint src2_stride_z,
+#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
@@ -3243,10 +3268,10 @@ __kernel void gemm_mm_interleaved_transposed_f16_acc32(IMAGE_DECLARATION(src0),
src_addr_b += offset_row_b;
// Reset accumulators
- float8 c00 = 0.0f;
- float8 c10 = 0.0f;
- float8 c20 = 0.0f;
- float8 c30 = 0.0f;
+ float8 c0 = 0.0f;
+ float8 c1 = 0.0f;
+ float8 c2 = 0.0f;
+ float8 c3 = 0.0f;
for(; src_addr_b <= (src_end_addr_b - (int)(16 * MULT_TRANSPOSE1XW_WIDTH)); src_addr_a += 8 * MULT_INTERLEAVE4X4_HEIGHT, src_addr_b += 16 * MULT_TRANSPOSE1XW_WIDTH)
{
@@ -3254,19 +3279,19 @@ __kernel void gemm_mm_interleaved_transposed_f16_acc32(IMAGE_DECLARATION(src0),
float4 a0 = convert_float4(vload4(0, src_addr_a));
float8 b0 = convert_float8(vload8(0, src_addr_b));
- c00 += (float8)a0.s0 * b0;
- c10 += (float8)a0.s1 * b0;
- c20 += (float8)a0.s2 * b0;
- c30 += (float8)a0.s3 * b0;
+ c0 += (float8)a0.s0 * b0;
+ c1 += (float8)a0.s1 * b0;
+ c2 += (float8)a0.s2 * b0;
+ c3 += (float8)a0.s3 * b0;
// Load values from matrix A (interleaved) and matrix B (transposed)
a0 = convert_float4(vload4(0, src_addr_a + 4 * MULT_INTERLEAVE4X4_HEIGHT));
b0 = convert_float8(vload8(0, src_addr_b + 8 * MULT_TRANSPOSE1XW_WIDTH));
- c00 += (float8)a0.s0 * b0;
- c10 += (float8)a0.s1 * b0;
- c20 += (float8)a0.s2 * b0;
- c30 += (float8)a0.s3 * b0;
+ c0 += (float8)a0.s0 * b0;
+ c1 += (float8)a0.s1 * b0;
+ c2 += (float8)a0.s2 * b0;
+ c3 += (float8)a0.s3 * b0;
}
for(; src_addr_b < src_end_addr_b; src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT, src_addr_b += 8 * MULT_TRANSPOSE1XW_WIDTH)
@@ -3275,40 +3300,20 @@ __kernel void gemm_mm_interleaved_transposed_f16_acc32(IMAGE_DECLARATION(src0),
float4 a0 = convert_float4(vload4(0, src_addr_a));
float8 b0 = convert_float8(vload8(0, src_addr_b));
- c00 += (float8)a0.s0 * b0;
- c10 += (float8)a0.s1 * b0;
- c20 += (float8)a0.s2 * b0;
- c30 += (float8)a0.s3 * b0;
+ c0 += (float8)a0.s0 * b0;
+ c1 += (float8)a0.s1 * b0;
+ c2 += (float8)a0.s2 * b0;
+ c3 += (float8)a0.s3 * b0;
}
// Compute destination address
Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
-#if defined(ALPHA)
- // Multiply by the weight of matrix product
- c00 = c00 * (float8)ALPHA;
- c10 = c10 * (float8)ALPHA;
- c20 = c20 * (float8)ALPHA;
- c30 = c30 * (float8)ALPHA;
-#endif // defined(ALPHA)
-
-#if defined(ADD_VEC_C)
- // *INDENT-OFF*
- // clang-format off
- __global half *src2_addr = (__global half *)(src2_ptr + src2_offset_first_element_in_bytes + get_global_id(0) * src2_step_x);
- float8 c0 = convert_float8(vload8(0, src2_addr));
- // clang-format on
- // *INDENT-ON*
-
- c00 += c0;
- c10 += c0;
- c20 += c0;
- c30 += c0;
-#endif /* defined(ADD_VEC_C) */
-
// Compute dst address
__global uchar *dst_addr = offset(&dst, 0, 0);
+ uint4 zout = 0;
+
#if defined(REINTERPRET_OUTPUT_AS_3D)
// Since we store a 2D output tile in a 3D tensor, we need to check when the plane changes across the z dimension
// in order to take into account the presence of possible cross plane paddings
@@ -3326,8 +3331,8 @@ __kernel void gemm_mm_interleaved_transposed_f16_acc32(IMAGE_DECLARATION(src0),
// |__________________|
// The plane (zout) is calculated dividing M (get_global_id(1) * 4) by HEIGHT_GEMM3D
- uint4 zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * 4)) / (uint4)HEIGHT_GEMM3D;
- zout = min(DEPTH_GEMM3D - 1, zout);
+ zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * 4)) / (uint4)HEIGHT_GEMM3D;
+ zout = min(DEPTH_GEMM3D - 1, zout);
// Add offset due to the cross plane paddings
zout *= (cross_plane_pad * dst_stride_y);
@@ -3335,44 +3340,86 @@ __kernel void gemm_mm_interleaved_transposed_f16_acc32(IMAGE_DECLARATION(src0),
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
-
- // Store 4x8 block
- vstore8(convert_half8(c00), 0, (__global half *)(dst_addr + 0 * dst_stride_y + zout.s0));
- vstore8(convert_half8(c10), 0, (__global half *)(dst_addr + 1 * dst_stride_y + zout.s1));
- vstore8(convert_half8(c20), 0, (__global half *)(dst_addr + 2 * dst_stride_y + zout.s2));
- vstore8(convert_half8(c30), 0, (__global half *)(dst_addr + 3 * dst_stride_y + zout.s3));
-
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
+#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+
+ // Multiply by the weight of matrix-matrix product and store the result
+#if defined(ALPHA)
+ SCALE_BLOCK(4, float, c, ALPHA);
+#endif // defined(ALPHA)
+
+#if defined(BETA)
+ REPEAT_VAR_INIT_TO_CONST(4, uint, zero, 0);
+
+#if defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)8 * sizeof(half));
+
+ LOAD_BLOCK(1, 8, half, bias, src2_addr, 0, src2_stride_y, zero);
+
+ float8 bias_f0 = convert_float8(bias0);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(1, float, bias_f, BETA);
+#endif // UNIT_BIAS
+
+ // c = c + bias[broadcasted]
+ ADD_BLOCK_BROADCAST(4, c, bias_f0);
+
+#else // defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)8 * sizeof(half)) + (get_global_id(1) * (uint)4 * src2_stride_y) + get_global_id(
+ 2) * src2_stride_z;
+
+ LOAD_BLOCK(4, 8, half, bias, src2_addr, 0, src2_stride_y, zero);
+
+ float8 bias_f0 = convert_float8(bias0);
+ float8 bias_f1 = convert_float8(bias1);
+ float8 bias_f2 = convert_float8(bias2);
+ float8 bias_f3 = convert_float8(bias3);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(4, float, bias_f, BETA);
+#endif // UNIT_BIAS
+
+ // c = c + bias
+ ADD_BLOCK(4, c, bias_f);
+
+#endif // defined(BROADCAST_BIAS)
+#endif // defined(BETA)
+
+ half8 c_h0 = convert_half8(c0);
+ half8 c_h1 = convert_half8(c1);
+ half8 c_h2 = convert_half8(c2);
+ half8 c_h3 = convert_half8(c3);
+
+#if defined(ACTIVATION_TYPE)
+ ACTIVATION_BLOCK(4, ACTIVATION_TYPE, half, c_h, A_VAL, B_VAL);
+#endif // defined(ACTIVATION_TYPE)
// Store 4x8 block
- vstore8(convert_half8(c00), 0, (__global half *)(dst_addr + 0 * dst_stride_y));
- vstore8(convert_half8(c10), 0, (__global half *)(dst_addr + 1 * dst_stride_y));
- vstore8(convert_half8(c20), 0, (__global half *)(dst_addr + 2 * dst_stride_y));
- vstore8(convert_half8(c30), 0, (__global half *)(dst_addr + 3 * dst_stride_y));
-#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+ vstore8(c_h0, 0, (__global half *)(dst_addr + 0 * dst_stride_y + zout.s0));
+ vstore8(c_h1, 0, (__global half *)(dst_addr + 1 * dst_stride_y + zout.s1));
+ vstore8(c_h2, 0, (__global half *)(dst_addr + 2 * dst_stride_y + zout.s2));
+ vstore8(c_h3, 0, (__global half *)(dst_addr + 3 * dst_stride_y + zout.s3));
}
-/** This OpenCL kernel optimized for Bifrost architectures computes the matrix multiplication between matrix A (src0) and matrix B (src1)
- * Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_16bit and @ref gemm_transpose1x8 before running the matrix multiplication
- *
- * Moreover, it can add a vector (src2) if the ADD_VEC_C parameter is passed at compile time.
+/** This OpenCL kernel optimized for Bifrost architectures computes the matrix multiplication between matrix A reshaped (src0) and matrix B reshaped (src1)
*
* @note The number of columns of matrix B and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
- * @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (i.e. -DMULT_TRANSPOSE1XW_WIDTH=2)
- * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (i.e. -DMULT_INTERLEAVE4X4_HEIGHT=2)
- * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
- * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
+ * @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (e.g. -DMULT_TRANSPOSE1XW_WIDTH=2)
+ * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (e.g. -DMULT_INTERLEAVE4X4_HEIGHT=2)
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (e.g. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (e.g. a = [K, M, 16, Batches], b = [N, K, 16])
*
- * @note In case the output has to be reinterpreted as a 3D tensor (i.e. output of convolution layer), the following information must be passed at compile time:
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * The activation function is performed after the bias addition
+ * @note In case the output has to be reinterpreted as a 3D tensor (e.g. output of convolution layer), the following information must be passed at compile time:
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
* -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns matrix A NOT reshaped
*
- * @note In case a 3rd input (src2) needs to be added, the ADD_VEC_C parameter has to be passed at compile time as -DADD_VEC_C
- *
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
@@ -3385,26 +3432,34 @@ __kernel void gemm_mm_interleaved_transposed_f16_acc32(IMAGE_DECLARATION(src0),
* @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes)
* @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix
- * @param[in] src2_ptr (Optional) Pointer to the source matrix. Supported data types: same as @p src0_ptr
- * @param[in] src2_stride_x (Optional) Stride of the source vector in X dimension (in bytes)
- * @param[in] src2_step_x (Optional) src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the source matrix
+ * @param[in] src2_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
+ * @param[in] src2_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
+ * @param[in] src2_step_x (Optional) src2_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src2_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
+ * @param[in] src2_step_y (Optional) src2_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src0_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
* @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
+ * @param[in] src0_stride_z Stride of the source matrix in Z dimension (in bytes)
+ * @param[in] src1_stride_z Stride of the source matrix in Z dimension (in bytes)
+ * @param[in] src2_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
*/
__kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0),
IMAGE_DECLARATION(src1),
-#if defined(ADD_VEC_C)
- VECTOR_DECLARATION(src2),
-#endif /* defined(ADD_VEC_C) */
+#if defined(BETA)
+ IMAGE_DECLARATION(src2),
+#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint src0_stride_z,
uint src1_stride_z,
+#if defined(BETA)
+ uint src2_stride_z,
+#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_OUTPUT_AS_3D)
,
@@ -3442,10 +3497,10 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
src_addr_b += offset_row_b;
// Reset accumulators
- half8 c00 = 0.0f;
- half8 c10 = 0.0f;
- half8 c20 = 0.0f;
- half8 c30 = 0.0f;
+ half8 c0 = 0.0f;
+ half8 c1 = 0.0f;
+ half8 c2 = 0.0f;
+ half8 c3 = 0.0f;
#define COLS_MTX_B (COLS_B / (8 * MULT_TRANSPOSE1XW_WIDTH))
@@ -3460,20 +3515,20 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
src_addr_a += 8 * MULT_INTERLEAVE4X4_HEIGHT;
src_addr_b += 8 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma((half8)a0.s0, b0, c00);
- c10 = fma((half8)a0.s1, b0, c10);
- c20 = fma((half8)a0.s2, b0, c20);
- c30 = fma((half8)a0.s3, b0, c30);
+ c0 = fma((half8)a0.s0, b0, c0);
+ c1 = fma((half8)a0.s1, b0, c1);
+ c2 = fma((half8)a0.s2, b0, c2);
+ c3 = fma((half8)a0.s3, b0, c3);
// Load values from matrix B (transposed)
b0 = vload8(0, src_addr_b);
src_addr_b += 8 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma((half8)a0.s4, b0, c00);
- c10 = fma((half8)a0.s5, b0, c10);
- c20 = fma((half8)a0.s6, b0, c20);
- c30 = fma((half8)a0.s7, b0, c30);
+ c0 = fma((half8)a0.s4, b0, c0);
+ c1 = fma((half8)a0.s5, b0, c1);
+ c2 = fma((half8)a0.s6, b0, c2);
+ c3 = fma((half8)a0.s7, b0, c3);
// Load values from matrix A (interleaved) and matrix B (transposed)
a0 = vload8(0, src_addr_a);
@@ -3482,20 +3537,20 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
src_addr_a += 8 * MULT_INTERLEAVE4X4_HEIGHT;
src_addr_b += 8 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma((half8)a0.s0, b0, c00);
- c10 = fma((half8)a0.s1, b0, c10);
- c20 = fma((half8)a0.s2, b0, c20);
- c30 = fma((half8)a0.s3, b0, c30);
+ c0 = fma((half8)a0.s0, b0, c0);
+ c1 = fma((half8)a0.s1, b0, c1);
+ c2 = fma((half8)a0.s2, b0, c2);
+ c3 = fma((half8)a0.s3, b0, c3);
// Load values from matrix B (transposed)
b0 = vload8(0, src_addr_b);
src_addr_b += 8 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma((half8)a0.s4, b0, c00);
- c10 = fma((half8)a0.s5, b0, c10);
- c20 = fma((half8)a0.s6, b0, c20);
- c30 = fma((half8)a0.s7, b0, c30);
+ c0 = fma((half8)a0.s4, b0, c0);
+ c1 = fma((half8)a0.s5, b0, c1);
+ c2 = fma((half8)a0.s6, b0, c2);
+ c3 = fma((half8)a0.s7, b0, c3);
#else // MULT_INTERLEAVE4X4_HEIGHT == 1
// Load values from matrix A (interleaved) and matrix B (transposed)
half4 a0 = vload4(0, src_addr_a);
@@ -3504,10 +3559,10 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT;
src_addr_b += 8 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma((half8)a0.s0, b0, c00);
- c10 = fma((half8)a0.s1, b0, c10);
- c20 = fma((half8)a0.s2, b0, c20);
- c30 = fma((half8)a0.s3, b0, c30);
+ c0 = fma((half8)a0.s0, b0, c0);
+ c1 = fma((half8)a0.s1, b0, c1);
+ c2 = fma((half8)a0.s2, b0, c2);
+ c3 = fma((half8)a0.s3, b0, c3);
// Load values from matrix A (interleaved) and matrix B (transposed)
a0 = vload4(0, src_addr_a);
@@ -3516,10 +3571,10 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT;
src_addr_b += 8 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma((half8)a0.s0, b0, c00);
- c10 = fma((half8)a0.s1, b0, c10);
- c20 = fma((half8)a0.s2, b0, c20);
- c30 = fma((half8)a0.s3, b0, c30);
+ c0 = fma((half8)a0.s0, b0, c0);
+ c1 = fma((half8)a0.s1, b0, c1);
+ c2 = fma((half8)a0.s2, b0, c2);
+ c3 = fma((half8)a0.s3, b0, c3);
// Load values from matrix A (interleaved) and matrix B (transposed)
a0 = vload4(0, src_addr_a);
@@ -3528,10 +3583,10 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT;
src_addr_b += 8 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma((half8)a0.s0, b0, c00);
- c10 = fma((half8)a0.s1, b0, c10);
- c20 = fma((half8)a0.s2, b0, c20);
- c30 = fma((half8)a0.s3, b0, c30);
+ c0 = fma((half8)a0.s0, b0, c0);
+ c1 = fma((half8)a0.s1, b0, c1);
+ c2 = fma((half8)a0.s2, b0, c2);
+ c3 = fma((half8)a0.s3, b0, c3);
// Load values from matrix A (interleaved) and matrix B (transposed)
a0 = vload4(0, src_addr_a);
@@ -3540,10 +3595,10 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT;
src_addr_b += 8 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma((half8)a0.s0, b0, c00);
- c10 = fma((half8)a0.s1, b0, c10);
- c20 = fma((half8)a0.s2, b0, c20);
- c30 = fma((half8)a0.s3, b0, c30);
+ c0 = fma((half8)a0.s0, b0, c0);
+ c1 = fma((half8)a0.s1, b0, c1);
+ c2 = fma((half8)a0.s2, b0, c2);
+ c3 = fma((half8)a0.s3, b0, c3);
#endif // MULT_INTERLEAVE4X4_HEIGHT == 1
}
@@ -3556,40 +3611,20 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
src_addr_a += 4 * MULT_INTERLEAVE4X4_HEIGHT;
src_addr_b += 8 * MULT_TRANSPOSE1XW_WIDTH;
- c00 = fma((half8)a0.s0, b0, c00);
- c10 = fma((half8)a0.s1, b0, c10);
- c20 = fma((half8)a0.s2, b0, c20);
- c30 = fma((half8)a0.s3, b0, c30);
+ c0 = fma((half8)a0.s0, b0, c0);
+ c1 = fma((half8)a0.s1, b0, c1);
+ c2 = fma((half8)a0.s2, b0, c2);
+ c3 = fma((half8)a0.s3, b0, c3);
}
// Compute destination address
Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
-#if defined(ALPHA)
- // Multiply by the weight of matrix product
- c00 = c00 * (half8)ALPHA;
- c10 = c10 * (half8)ALPHA;
- c20 = c20 * (half8)ALPHA;
- c30 = c30 * (half8)ALPHA;
-#endif // defined(ALPHA)
-
-#if defined(ADD_VEC_C)
- // *INDENT-OFF*
- // clang-format off
- __global half *src2_addr = (__global half *)(src2_ptr + src2_offset_first_element_in_bytes + get_global_id(0) * src2_step_x);
- half8 c0 = vload8(0, src2_addr);
- // clang-format on
- // *INDENT-ON*
-
- c00 += c0;
- c10 += c0;
- c20 += c0;
- c30 += c0;
-#endif /* defined(ADD_VEC_C) */
-
// Compute dst address
__global uchar *dst_addr = offset(&dst, 0, 0);
+ uint4 zout = 0;
+
#if defined(REINTERPRET_OUTPUT_AS_3D)
// Since we store a 2D output tile in a 3D tensor, we need to check when the plane changes across the z dimension
// in order to take into account the presence of possible cross plane paddings
@@ -3607,8 +3642,8 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
// |__________________|
// The plane (zout) is calculated dividing M (get_global_id(1) * 4) by HEIGHT_GEMM3D
- uint4 zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * 4)) / (uint4)HEIGHT_GEMM3D;
- zout = min(DEPTH_GEMM3D - 1, zout);
+ zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * 4)) / (uint4)HEIGHT_GEMM3D;
+ zout = min(DEPTH_GEMM3D - 1, zout);
// Add offset due to the cross plane paddings
zout *= (cross_plane_pad * dst_stride_y);
@@ -3616,23 +3651,57 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
-
- // Store 4x8 block
- vstore8(c00, 0, (__global half *)(dst_addr + 0 * dst_stride_y + zout.s0));
- vstore8(c10, 0, (__global half *)(dst_addr + 1 * dst_stride_y + zout.s1));
- vstore8(c20, 0, (__global half *)(dst_addr + 2 * dst_stride_y + zout.s2));
- vstore8(c30, 0, (__global half *)(dst_addr + 3 * dst_stride_y + zout.s3));
-
#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
+#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+
+ // Multiply by the weight of matrix-matrix product and store the result
+#if defined(ALPHA)
+ SCALE_BLOCK(4, half, c, ALPHA);
+#endif // defined(ALPHA)
+
+ // Add beta*bias
+#if defined(BETA)
+ REPEAT_VAR_INIT_TO_CONST(4, uint, zero, 0);
+
+#if defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)8 * sizeof(half));
+
+ LOAD_BLOCK(1, 8, half, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(1, half, bias, BETA);
+#endif // UNIT_BIAS
+
+ // c = c + bias[broadcasted]
+ ADD_BLOCK_BROADCAST(4, c, bias0);
+
+#else // defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)8 * sizeof(half)) + (get_global_id(1) * (uint)4 * src2_stride_y) + get_global_id(
+ 2) * src2_stride_z;
+
+ LOAD_BLOCK(4, 8, half, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(4, half, bias, BETA);
+#endif // UNIT_BIAS
+
+ // c = c + bias
+ ADD_BLOCK(4, c, bias);
+
+#endif // defined(BROADCAST_BIAS)
+#endif // defined(BETA)
+
+#if defined(ACTIVATION_TYPE)
+ ACTIVATION_BLOCK(4, ACTIVATION_TYPE, half, c, A_VAL, B_VAL);
+#endif // defined(ACTIVATION_TYPE)
// Store 4x8 block
- vstore8(c00, 0, (__global half *)(dst_addr + 0 * dst_stride_y));
- vstore8(c10, 0, (__global half *)(dst_addr + 1 * dst_stride_y));
- vstore8(c20, 0, (__global half *)(dst_addr + 2 * dst_stride_y));
- vstore8(c30, 0, (__global half *)(dst_addr + 3 * dst_stride_y));
-#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+ vstore8(c0, 0, (__global half *)(dst_addr + 0 * dst_stride_y + zout.s0));
+ vstore8(c1, 0, (__global half *)(dst_addr + 1 * dst_stride_y + zout.s1));
+ vstore8(c2, 0, (__global half *)(dst_addr + 2 * dst_stride_y + zout.s2));
+ vstore8(c3, 0, (__global half *)(dst_addr + 3 * dst_stride_y + zout.s3));
}
// Undefine local defines
@@ -3647,15 +3716,15 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
#define VECTOR_TYPE VEC_DATA_TYPE(DATA_TYPE, NUM_ELEMS_PROCESSED_PER_THREAD_X)
/** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not been reshaped.
*
- * Moreover, it can add a vector (src2) if the ADD_VEC_C parameter is passed at compile time.
- *
* @note This OpenCL kernel works with floating point data types (F16/F32)
* @note The floating point data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=float)
* @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y
* @note The number of matrix A columns and the optional alpha's value need to be passed at compile time using -DCOLS_A and -DALPHA
- * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
- * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (e.g. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (e.g. a = [K, M, 16, Batches], b = [N, K, 16])
*
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
@@ -3663,8 +3732,6 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns matrix A NOT reshaped
*
- * @note In case a 3rd input (src2) needs to be added, the ADD_VEC_C parameter has to be passed at compile time as -DADD_VEC_C
- *
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16/F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
@@ -3677,10 +3744,12 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
* @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes)
* @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix
- * @param[in] src2_ptr (Optional) Pointer to the source matrix. Supported data types: same as @p src0_ptr
- * @param[in] src2_stride_x (Optional) Stride of the source vector in X dimension (in bytes)
- * @param[in] src2_step_x (Optional) src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the source matrix
+ * @param[in] src2_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
+ * @param[in] src2_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
+ * @param[in] src2_step_x (Optional) src2_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src2_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
+ * @param[in] src2_step_y (Optional) src2_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src0_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes)
@@ -3689,18 +3758,22 @@ __kernel void gemm_mm_interleaved_transposed_f16_bifrost(IMAGE_DECLARATION(src0)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] src0_stride_z Stride of the source matrix in Z dimension (in bytes)
* @param[in] src1_stride_z Stride of the source matrix in Z dimension (in bytes)
+ * @param[in] src2_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] src_cross_plane_pad (Optional) Bottom paddings in unit of elements for the input tensor (only if defined REINTERPRET_INPUT_AS_3D)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements for the output tensor (only if defined REINTERPRET_OUTPUT_AS_3D)
*/
__kernel void gemm_mm_floating_point(IMAGE_DECLARATION(src0),
IMAGE_DECLARATION(src1),
-#if defined(ADD_VEC_C)
- VECTOR_DECLARATION(src2),
-#endif /* defined(ADD_VEC_C) */
+#if defined(BETA)
+ IMAGE_DECLARATION(src2),
+#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint src0_stride_z,
uint src1_stride_z,
+#if defined(BETA)
+ uint src2_stride_z,
+#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_INPUT_AS_3D)
,
@@ -3865,49 +3938,18 @@ __kernel void gemm_mm_floating_point(IMAGE_DECLARATION(src0),
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
}
+ int z = get_global_id(2);
+
// Compute destination address
Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
// Compute dst address
__global uchar *dst_addr = offset(&dst, 0, 0);
- // Multiply by the weight of matrix-matrix product and store the result
-#if defined(ALPHA)
- acc0 = acc0 * (VECTOR_TYPE)ALPHA;
-#endif // defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 && defined(ALPHA)
- acc1 = acc1 * (VECTOR_TYPE)ALPHA;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 && defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 && defined(ALPHA)
- acc2 = acc2 * (VECTOR_TYPE)ALPHA;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 && defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 && defined(ALPHA)
- acc3 = acc3 * (VECTOR_TYPE)ALPHA;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 && defined(ALPHA)
-
-#if defined(ADD_VEC_C)
- // *INDENT-OFF*
- // clang-format off
- __global DATA_TYPE *src2_addr = (__global DATA_TYPE *)(src2_ptr + src2_offset_first_element_in_bytes + get_global_id(0) * src2_step_x);
- VECTOR_TYPE c0 = VLOAD(NUM_ELEMS_PROCESSED_PER_THREAD_X)(0, src2_addr);
- // clang-format on
- // *INDENT-ON*
-
- acc0 += c0;
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- acc1 += c0;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- acc2 += c0;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- acc3 += c0;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-#endif /* defined(ADD_VEC_C) */
-
- int z = get_global_id(2);
+ uint4 zout = 0;
#if defined(REINTERPRET_OUTPUT_AS_3D)
+
// Since we store a 2D output tile in a 3D tensor, we need to check when the plane changes across the z dimension
// in order to take into account the presence of possible cross plane paddings
//
@@ -3924,8 +3966,8 @@ __kernel void gemm_mm_floating_point(IMAGE_DECLARATION(src0),
// |__________________|
// The plane (zout) is calculated dividing M (get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y) by HEIGHT_GEMM3D
- uint4 zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y)) / (uint4)HEIGHT_GEMM3D;
- zout = min(DEPTH_GEMM3D - 1, zout);
+ zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y)) / (uint4)HEIGHT_GEMM3D;
+ zout = min(DEPTH_GEMM3D - 1, zout);
// Add offset due to the cross plane paddings
zout *= (dst_cross_plane_pad * dst_stride_y);
@@ -3933,44 +3975,69 @@ __kernel void gemm_mm_floating_point(IMAGE_DECLARATION(src0),
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
-
- // Store output block
- STORE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, NUM_ELEMS_PROCESSED_PER_THREAD_X, DATA_TYPE, acc, dst_addr, dst_stride_y, zout.s);
-#else // defined(REINTERPRET_OUTPUT_AS_3D)
+#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
+#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+
+ // Multiply by the weight of matrix-matrix product and store the result
+#if defined(ALPHA)
+ SCALE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, DATA_TYPE, acc, ALPHA);
+#endif // defined(ALPHA)
+
+ // Add beta*bias
+#if defined(BETA)
+ REPEAT_VAR_INIT_TO_CONST(NUM_ELEMS_PROCESSED_PER_THREAD_Y, uint, zero, 0);
+
+#if defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)NUM_ELEMS_PROCESSED_PER_THREAD_X * sizeof(DATA_TYPE));
+
+ LOAD_BLOCK(1, NUM_ELEMS_PROCESSED_PER_THREAD_X, DATA_TYPE, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(1, DATA_TYPE, bias, BETA);
+#endif // UNIT_BIAS
+
+ // c = c + bias[broadcasted]
+ ADD_BLOCK_BROADCAST(NUM_ELEMS_PROCESSED_PER_THREAD_Y, acc, bias0);
+
+#else // defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)NUM_ELEMS_PROCESSED_PER_THREAD_X * sizeof(DATA_TYPE)) + (get_global_id(1) *
+ (uint)NUM_ELEMS_PROCESSED_PER_THREAD_Y * src2_stride_y) + get_global_id(2) * src2_stride_z;
+
+ LOAD_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, NUM_ELEMS_PROCESSED_PER_THREAD_X, DATA_TYPE, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, DATA_TYPE, bias, BETA);
+#endif // UNIT_BIAS
+
+ // c = c + bias
+ ADD_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, acc, bias);
+
+#endif // defined(BROADCAST_BIAS)
+#endif // defined(BETA)
+
+#if defined(ACTIVATION_TYPE)
+ ACTIVATION_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, ACTIVATION_TYPE, DATA_TYPE, acc, A_VAL, B_VAL);
+#endif // defined(ACTIVATION_TYPE)
// Store output block
- VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X)
- (acc0, 0, (__global DATA_TYPE *)(dst_addr + 0 * dst_stride_y));
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X)
- (acc1, 0, (__global DATA_TYPE *)(dst_addr + 1 * dst_stride_y));
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X)
- (acc2, 0, (__global DATA_TYPE *)(dst_addr + 2 * dst_stride_y));
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X)
- (acc3, 0, (__global DATA_TYPE *)(dst_addr + 3 * dst_stride_y));
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+ STORE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, NUM_ELEMS_PROCESSED_PER_THREAD_X, DATA_TYPE, acc, dst_addr, dst_stride_y, zout.s);
}
#endif // defined(DATA_TYPE)
/** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not been reshaped
*
- * Moreover, it can add a vector (src2) if the ADD_VEC_C parameter is passed at compile time.
- *
* @note This OpenCL kernel works with the 32-bit floating point data type (float) and uses the fma units.
* @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y.
* This kernel optimally uses -DNUM_ELEMS_PROCESSED_PER_THREAD_X=4.
* @note The number of matrix A columns must be passed at compile time using -DCOLS_A.
* @note The optional value of scalar alpha is passed at compile time using -DALPHA=alpha
- * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
- * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (e.g. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (e.g. a = [K, M, 16, Batches], b = [N, K, 16])
*
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
@@ -3978,9 +4045,7 @@ __kernel void gemm_mm_floating_point(IMAGE_DECLARATION(src0),
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns matrix A NOT reshaped
*
- * @note In case a 3rd input (src2) needs to be added, the ADD_VEC_C parameter has to be passed at compile time as -DADD_VEC_C
- *
- * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16/F32
+ * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] src0_stride_y Stride of the source matrix in Y dimension (in bytes)
@@ -3992,10 +4057,12 @@ __kernel void gemm_mm_floating_point(IMAGE_DECLARATION(src0),
* @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes)
* @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix
- * @param[in] src2_ptr (Optional) Pointer to the source matrix. Supported data types: same as @p src0_ptr
- * @param[in] src2_stride_x (Optional) Stride of the source vector in X dimension (in bytes)
- * @param[in] src2_step_x (Optional) src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the source matrix
+ * @param[in] src2_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
+ * @param[in] src2_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
+ * @param[in] src2_step_x (Optional) src2_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src2_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
+ * @param[in] src2_step_y (Optional) src2_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src0_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes)
@@ -4004,18 +4071,22 @@ __kernel void gemm_mm_floating_point(IMAGE_DECLARATION(src0),
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] src0_stride_z Stride of the source matrix in Z dimension (in bytes)
* @param[in] src1_stride_z Stride of the source matrix in Z dimension (in bytes)
+ * @param[in] src2_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] src_cross_plane_pad (Optional) Bottom paddings in unit of elements for the input tensor (only if defined REINTERPRET_INPUT_AS_3D)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
*/
__kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
IMAGE_DECLARATION(src1),
-#if defined(ADD_VEC_C)
- VECTOR_DECLARATION(src2),
-#endif /* defined(ADD_VEC_C) */
+#if defined(BETA)
+ IMAGE_DECLARATION(src2),
+#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint src0_stride_z,
uint src1_stride_z,
+#if defined(BETA)
+ uint src2_stride_z,
+#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_INPUT_AS_3D)
,
@@ -4080,30 +4151,18 @@ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
#endif // defined(MATRIX_B_DEPTH)
// Initialize accumulators
- float acc00 = 0.0f;
- float acc01 = 0.0f;
- float acc02 = 0.0f;
- float acc03 = 0.0f;
+ float4 acc0 = 0.0f;
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- float acc10 = 0.0f;
- float acc11 = 0.0f;
- float acc12 = 0.0f;
- float acc13 = 0.0f;
+ float4 acc1 = 0.0f;
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- float acc20 = 0.0f;
- float acc21 = 0.0f;
- float acc22 = 0.0f;
- float acc23 = 0.0f;
+ float4 acc2 = 0.0f;
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- float acc30 = 0.0f;
- float acc31 = 0.0f;
- float acc32 = 0.0f;
- float acc33 = 0.0f;
+ float4 acc3 = 0.0f;
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
// A and B src indices get incremented at the same time.
@@ -4131,33 +4190,33 @@ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
src_addr.s1 += src1_stride_y;
// Multiply and accumulate
- acc00 = fma(a0.s0, b0.s0, acc00);
- acc01 = fma(a0.s0, b0.s1, acc01);
- acc02 = fma(a0.s0, b0.s2, acc02);
- acc03 = fma(a0.s0, b0.s3, acc03);
+ acc0.s0 = fma(a0.s0, b0.s0, acc0.s0);
+ acc0.s1 = fma(a0.s0, b0.s1, acc0.s1);
+ acc0.s2 = fma(a0.s0, b0.s2, acc0.s2);
+ acc0.s3 = fma(a0.s0, b0.s3, acc0.s3);
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- acc10 = fma(a1.s0, b0.s0, acc10);
- acc11 = fma(a1.s0, b0.s1, acc11);
- acc12 = fma(a1.s0, b0.s2, acc12);
- acc13 = fma(a1.s0, b0.s3, acc13);
+ acc1.s0 = fma(a1.s0, b0.s0, acc1.s0);
+ acc1.s1 = fma(a1.s0, b0.s1, acc1.s1);
+ acc1.s2 = fma(a1.s0, b0.s2, acc1.s2);
+ acc1.s3 = fma(a1.s0, b0.s3, acc1.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- acc20 = fma(a2.s0, b0.s0, acc20);
- acc21 = fma(a2.s0, b0.s1, acc21);
- acc22 = fma(a2.s0, b0.s2, acc22);
- acc23 = fma(a2.s0, b0.s3, acc23);
+ acc2.s0 = fma(a2.s0, b0.s0, acc2.s0);
+ acc2.s1 = fma(a2.s0, b0.s1, acc2.s1);
+ acc2.s2 = fma(a2.s0, b0.s2, acc2.s2);
+ acc2.s3 = fma(a2.s0, b0.s3, acc2.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- acc30 = fma(a3.s0, b0.s0, acc30);
- acc31 = fma(a3.s0, b0.s1, acc31);
- acc32 = fma(a3.s0, b0.s2, acc32);
- acc33 = fma(a3.s0, b0.s3, acc33);
+ acc3.s0 = fma(a3.s0, b0.s0, acc3.s0);
+ acc3.s1 = fma(a3.s0, b0.s1, acc3.s1);
+ acc3.s2 = fma(a3.s0, b0.s2, acc3.s2);
+ acc3.s3 = fma(a3.s0, b0.s3, acc3.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
// Load values from matrix A and matrix B
@@ -4165,33 +4224,33 @@ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
src_addr.s1 += src1_stride_y;
// Multiply and accumulate
- acc00 = fma(a0.s1, b0.s0, acc00);
- acc01 = fma(a0.s1, b0.s1, acc01);
- acc02 = fma(a0.s1, b0.s2, acc02);
- acc03 = fma(a0.s1, b0.s3, acc03);
+ acc0.s0 = fma(a0.s1, b0.s0, acc0.s0);
+ acc0.s1 = fma(a0.s1, b0.s1, acc0.s1);
+ acc0.s2 = fma(a0.s1, b0.s2, acc0.s2);
+ acc0.s3 = fma(a0.s1, b0.s3, acc0.s3);
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- acc10 = fma(a1.s1, b0.s0, acc10);
- acc11 = fma(a1.s1, b0.s1, acc11);
- acc12 = fma(a1.s1, b0.s2, acc12);
- acc13 = fma(a1.s1, b0.s3, acc13);
+ acc1.s0 = fma(a1.s1, b0.s0, acc1.s0);
+ acc1.s1 = fma(a1.s1, b0.s1, acc1.s1);
+ acc1.s2 = fma(a1.s1, b0.s2, acc1.s2);
+ acc1.s3 = fma(a1.s1, b0.s3, acc1.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- acc20 = fma(a2.s1, b0.s0, acc20);
- acc21 = fma(a2.s1, b0.s1, acc21);
- acc22 = fma(a2.s1, b0.s2, acc22);
- acc23 = fma(a2.s1, b0.s3, acc23);
+ acc2.s0 = fma(a2.s1, b0.s0, acc2.s0);
+ acc2.s1 = fma(a2.s1, b0.s1, acc2.s1);
+ acc2.s2 = fma(a2.s1, b0.s2, acc2.s2);
+ acc2.s3 = fma(a2.s1, b0.s3, acc2.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- acc30 = fma(a3.s1, b0.s0, acc30);
- acc31 = fma(a3.s1, b0.s1, acc31);
- acc32 = fma(a3.s1, b0.s2, acc32);
- acc33 = fma(a3.s1, b0.s3, acc33);
+ acc3.s0 = fma(a3.s1, b0.s0, acc3.s0);
+ acc3.s1 = fma(a3.s1, b0.s1, acc3.s1);
+ acc3.s2 = fma(a3.s1, b0.s2, acc3.s2);
+ acc3.s3 = fma(a3.s1, b0.s3, acc3.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
// Load values from matrix A and matrix B
@@ -4199,33 +4258,33 @@ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
src_addr.s1 += src1_stride_y;
// Multiply and accumulate
- acc00 = fma(a0.s2, b0.s0, acc00);
- acc01 = fma(a0.s2, b0.s1, acc01);
- acc02 = fma(a0.s2, b0.s2, acc02);
- acc03 = fma(a0.s2, b0.s3, acc03);
+ acc0.s0 = fma(a0.s2, b0.s0, acc0.s0);
+ acc0.s1 = fma(a0.s2, b0.s1, acc0.s1);
+ acc0.s2 = fma(a0.s2, b0.s2, acc0.s2);
+ acc0.s3 = fma(a0.s2, b0.s3, acc0.s3);
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- acc10 = fma(a1.s2, b0.s0, acc10);
- acc11 = fma(a1.s2, b0.s1, acc11);
- acc12 = fma(a1.s2, b0.s2, acc12);
- acc13 = fma(a1.s2, b0.s3, acc13);
+ acc1.s0 = fma(a1.s2, b0.s0, acc1.s0);
+ acc1.s1 = fma(a1.s2, b0.s1, acc1.s1);
+ acc1.s2 = fma(a1.s2, b0.s2, acc1.s2);
+ acc1.s3 = fma(a1.s2, b0.s3, acc1.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- acc20 = fma(a2.s2, b0.s0, acc20);
- acc21 = fma(a2.s2, b0.s1, acc21);
- acc22 = fma(a2.s2, b0.s2, acc22);
- acc23 = fma(a2.s2, b0.s3, acc23);
+ acc2.s0 = fma(a2.s2, b0.s0, acc2.s0);
+ acc2.s1 = fma(a2.s2, b0.s1, acc2.s1);
+ acc2.s2 = fma(a2.s2, b0.s2, acc2.s2);
+ acc2.s3 = fma(a2.s2, b0.s3, acc2.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- acc30 = fma(a3.s2, b0.s0, acc30);
- acc31 = fma(a3.s2, b0.s1, acc31);
- acc32 = fma(a3.s2, b0.s2, acc32);
- acc33 = fma(a3.s2, b0.s3, acc33);
+ acc3.s0 = fma(a3.s2, b0.s0, acc3.s0);
+ acc3.s1 = fma(a3.s2, b0.s1, acc3.s1);
+ acc3.s2 = fma(a3.s2, b0.s2, acc3.s2);
+ acc3.s3 = fma(a3.s2, b0.s3, acc3.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
// Load values from matrix A and matrix B
@@ -4233,33 +4292,33 @@ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
src_addr.s1 += src1_stride_y;
// Multiply and accumulate
- acc00 = fma(a0.s3, b0.s0, acc00);
- acc01 = fma(a0.s3, b0.s1, acc01);
- acc02 = fma(a0.s3, b0.s2, acc02);
- acc03 = fma(a0.s3, b0.s3, acc03);
+ acc0.s0 = fma(a0.s3, b0.s0, acc0.s0);
+ acc0.s1 = fma(a0.s3, b0.s1, acc0.s1);
+ acc0.s2 = fma(a0.s3, b0.s2, acc0.s2);
+ acc0.s3 = fma(a0.s3, b0.s3, acc0.s3);
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- acc10 = fma(a1.s3, b0.s0, acc10);
- acc11 = fma(a1.s3, b0.s1, acc11);
- acc12 = fma(a1.s3, b0.s2, acc12);
- acc13 = fma(a1.s3, b0.s3, acc13);
+ acc1.s0 = fma(a1.s3, b0.s0, acc1.s0);
+ acc1.s1 = fma(a1.s3, b0.s1, acc1.s1);
+ acc1.s2 = fma(a1.s3, b0.s2, acc1.s2);
+ acc1.s3 = fma(a1.s3, b0.s3, acc1.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- acc20 = fma(a2.s3, b0.s0, acc20);
- acc21 = fma(a2.s3, b0.s1, acc21);
- acc22 = fma(a2.s3, b0.s2, acc22);
- acc23 = fma(a2.s3, b0.s3, acc23);
+ acc2.s0 = fma(a2.s3, b0.s0, acc2.s0);
+ acc2.s1 = fma(a2.s3, b0.s1, acc2.s1);
+ acc2.s2 = fma(a2.s3, b0.s2, acc2.s2);
+ acc2.s3 = fma(a2.s3, b0.s3, acc2.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- acc30 = fma(a3.s3, b0.s0, acc30);
- acc31 = fma(a3.s3, b0.s1, acc31);
- acc32 = fma(a3.s3, b0.s2, acc32);
- acc33 = fma(a3.s3, b0.s3, acc33);
+ acc3.s0 = fma(a3.s3, b0.s0, acc3.s0);
+ acc3.s1 = fma(a3.s3, b0.s1, acc3.s1);
+ acc3.s2 = fma(a3.s3, b0.s2, acc3.s2);
+ acc3.s3 = fma(a3.s3, b0.s3, acc3.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
src_addr.s0 += 4 * sizeof(float);
@@ -4298,27 +4357,27 @@ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
src_addr.s1 += src1_stride_y;
// Multiply and accumulate
- acc00 = fma(a0, b0.s0, acc00);
- acc01 = fma(a0, b0.s1, acc01);
- acc02 = fma(a0, b0.s2, acc02);
- acc03 = fma(a0, b0.s3, acc03);
+ acc0.s0 = fma(a0, b0.s0, acc0.s0);
+ acc0.s1 = fma(a0, b0.s1, acc0.s1);
+ acc0.s2 = fma(a0, b0.s2, acc0.s2);
+ acc0.s3 = fma(a0, b0.s3, acc0.s3);
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- acc10 = fma(a1, b0.s0, acc10);
- acc11 = fma(a1, b0.s1, acc11);
- acc12 = fma(a1, b0.s2, acc12);
- acc13 = fma(a1, b0.s3, acc13);
+ acc1.s0 = fma(a1, b0.s0, acc1.s0);
+ acc1.s1 = fma(a1, b0.s1, acc1.s1);
+ acc1.s2 = fma(a1, b0.s2, acc1.s2);
+ acc1.s3 = fma(a1, b0.s3, acc1.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- acc20 = fma(a2, b0.s0, acc20);
- acc21 = fma(a2, b0.s1, acc21);
- acc22 = fma(a2, b0.s2, acc22);
- acc23 = fma(a2, b0.s3, acc23);
+ acc2.s0 = fma(a2, b0.s0, acc2.s0);
+ acc2.s1 = fma(a2, b0.s1, acc2.s1);
+ acc2.s2 = fma(a2, b0.s2, acc2.s2);
+ acc2.s3 = fma(a2, b0.s3, acc2.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- acc30 = fma(a3, b0.s0, acc30);
- acc31 = fma(a3, b0.s1, acc31);
- acc32 = fma(a3, b0.s2, acc32);
- acc33 = fma(a3, b0.s3, acc33);
+ acc3.s0 = fma(a3, b0.s0, acc3.s0);
+ acc3.s1 = fma(a3, b0.s1, acc3.s1);
+ acc3.s2 = fma(a3, b0.s2, acc3.s2);
+ acc3.s3 = fma(a3, b0.s3, acc3.s3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
src_addr.s0 += sizeof(float);
@@ -4329,62 +4388,10 @@ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
// Compute destination address
Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
- // Multiply by the weight of matrix-matrix product and store the result
-#if defined(ALPHA)
- acc00 = acc00 * ALPHA;
- acc01 = acc01 * ALPHA;
- acc02 = acc02 * ALPHA;
- acc03 = acc03 * ALPHA;
-#endif // defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 && defined(ALPHA)
- acc10 = acc10 * ALPHA;
- acc11 = acc11 * ALPHA;
- acc12 = acc12 * ALPHA;
- acc13 = acc13 * ALPHA;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 && defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 && defined(ALPHA)
- acc20 = acc20 * ALPHA;
- acc21 = acc21 * ALPHA;
- acc22 = acc22 * ALPHA;
- acc23 = acc23 * ALPHA;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 && defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 && defined(ALPHA)
- acc30 = acc30 * ALPHA;
- acc31 = acc31 * ALPHA;
- acc32 = acc32 * ALPHA;
- acc33 = acc33 * ALPHA;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 && defined(ALPHA)
-
// Compute dst address
__global uchar *dst_addr = offset(&dst, 0, 0);
-#if defined(ADD_VEC_C)
- __global float *src2_addr = (__global float *)(src2_ptr + src2_offset_first_element_in_bytes + get_global_id(0) * src2_step_x);
- float4 c0 = vload4(0, src2_addr);
-
- acc00 += c0.s0;
- acc01 += c0.s1;
- acc02 += c0.s2;
- acc03 += c0.s3;
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- acc10 += c0.s0;
- acc11 += c0.s1;
- acc12 += c0.s2;
- acc13 += c0.s3;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- acc20 += c0.s0;
- acc21 += c0.s1;
- acc22 += c0.s2;
- acc23 += c0.s3;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- acc30 += c0.s0;
- acc31 += c0.s1;
- acc32 += c0.s2;
- acc33 += c0.s3;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-#endif /* defined(ADD_VEC_C) */
+ uint4 zout = 0;
#if defined(REINTERPRET_OUTPUT_AS_3D)
// Since we store a 2D output tile in a 3D tensor, we need to check when the plane changes across the z dimension
@@ -4403,8 +4410,8 @@ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
// |__________________|
// The plane (zout) is calculated dividing M (get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y) by HEIGHT_GEMM3D
- uint4 zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y)) / (uint4)HEIGHT_GEMM3D;
- zout = min(DEPTH_GEMM3D - 1, zout);
+ zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y)) / (uint4)HEIGHT_GEMM3D;
+ zout = min(DEPTH_GEMM3D - 1, zout);
// Add offset due to the cross plane paddings
zout *= (dst_cross_plane_pad * dst_stride_y);
@@ -4412,50 +4419,78 @@ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
-
- // Store the output block
- vstore4((float4)(acc00, acc01, acc02, acc03), 0, (__global float *)(dst_addr + 0 * dst_stride_y + zout.s0));
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- vstore4((float4)(acc10, acc11, acc12, acc13), 0, (__global float *)(dst_addr + 1 * dst_stride_y + zout.s1));
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- vstore4((float4)(acc20, acc21, acc22, acc23), 0, (__global float *)(dst_addr + 2 * dst_stride_y + zout.s2));
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- vstore4((float4)(acc30, acc31, acc32, acc33), 0, (__global float *)(dst_addr + 3 * dst_stride_y + zout.s3));
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-
-#else // defined(REINTERPRET_OUTPUT_AS_3D)
+#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
+#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+
+ // Multiply by the weight of matrix-matrix product and store the result
+#if defined(ALPHA)
+ SCALE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, float, acc, ALPHA);
+#endif // defined(ALPHA)
+
+ // Add beta*bias
+#if defined(BETA)
+ REPEAT_VAR_INIT_TO_CONST(NUM_ELEMS_PROCESSED_PER_THREAD_Y, uint, zero, 0);
+
+#if defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)4 * sizeof(float));
+
+ LOAD_BLOCK(1, 4, float, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(1, float, bias, BETA);
+#endif // UNIT_BIAS
+
+ // acc = acc + bias[broadcasted]
+ ADD_BLOCK_BROADCAST(NUM_ELEMS_PROCESSED_PER_THREAD_Y, acc, bias0);
+
+#else // defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)4 * sizeof(float)) + (get_global_id(1) *
+ (uint)NUM_ELEMS_PROCESSED_PER_THREAD_Y * src2_stride_y) + get_global_id(2) * src2_stride_z;
+
+ LOAD_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, 4, float, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, float, bias, BETA);
+#endif // UNIT_BIAS
+
+ // acc = acc + bias
+ ADD_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, acc, bias);
+
+#endif // defined(BROADCAST_BIAS)
+#endif // defined(BETA)
+
+#if defined(ACTIVATION_TYPE)
+ ACTIVATION_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, ACTIVATION_TYPE, float, acc, A_VAL, B_VAL);
+#endif // defined(ACTIVATION_TYPE)
// Store the output block
- vstore4((float4)(acc00, acc01, acc02, acc03), 0, (__global float *)(dst_addr + 0 * dst_stride_y));
+ vstore4(acc0, 0, (__global float *)(dst_addr + 0 * dst_stride_y + zout.s0));
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- vstore4((float4)(acc10, acc11, acc12, acc13), 0, (__global float *)(dst_addr + 1 * dst_stride_y));
+ vstore4(acc1, 0, (__global float *)(dst_addr + 1 * dst_stride_y + zout.s1));
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- vstore4((float4)(acc20, acc21, acc22, acc23), 0, (__global float *)(dst_addr + 2 * dst_stride_y));
+ vstore4(acc2, 0, (__global float *)(dst_addr + 2 * dst_stride_y + zout.s2));
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- vstore4((float4)(acc30, acc31, acc32, acc33), 0, (__global float *)(dst_addr + 3 * dst_stride_y));
+ vstore4(acc3, 0, (__global float *)(dst_addr + 3 * dst_stride_y + zout.s3));
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-#endif // defined(REINTERPRET_OUTPUT_AS_3D)
}
/** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not been reshaped
*
- * Moreover, it can add a vector (src2) if the ADD_VEC_C parameter is passed at compile time.
- *
* @note This OpenCL kernel works with the 32-bit floating point data type (float) and uses the fma units.
* This OpenCL kernel is optimized for Bifrost when the number of matrix B columns is less or equal to 1000.
* @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y.
* This kernel optimally uses -DNUM_ELEMS_PROCESSED_PER_THREAD_X=2.
* @note The number of matrix A columns must be passed at compile time using -DCOLS_A.
* @note The optional value of scalar alpha is passed at compile time using -DALPHA=alpha if alpha!=1.0f.
- * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
- * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (e.g. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (e.g. a = [K, M, 16, Batches], b = [N, K, 16])
*
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
@@ -4463,9 +4498,7 @@ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns matrix A NOT reshaped
*
- * @note In case a 3rd input (src2) needs to be added, the ADD_VEC_C parameter has to be passed at compile time as -DADD_VEC_C
- *
- * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16/F32
+ * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] src0_stride_y Stride of the source matrix in Y dimension (in bytes)
@@ -4477,10 +4510,12 @@ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
* @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes)
* @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix
- * @param[in] src2_ptr (Optional) Pointer to the source matrix. Supported data types: same as @p src0_ptr
- * @param[in] src2_stride_x (Optional) Stride of the source vector in X dimension (in bytes)
- * @param[in] src2_step_x (Optional) src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the source matrix
+ * @param[in] src2_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
+ * @param[in] src2_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
+ * @param[in] src2_step_x (Optional) src2_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src2_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
+ * @param[in] src2_step_y (Optional) src2_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src0_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes)
@@ -4489,18 +4524,22 @@ __kernel void gemm_mm_floating_point_f32_bifrost(IMAGE_DECLARATION(src0),
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] src0_stride_z Stride of the source matrix in Z dimension (in bytes)
* @param[in] src1_stride_z Stride of the source matrix in Z dimension (in bytes)
+ * @param[in] src2_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] src_cross_plane_pad (Optional) Bottom paddings in unit of elements for the input tensor (only if defined REINTERPRET_INPUT_AS_3D)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
*/
__kernel void gemm_mm_floating_point_f32_bifrost_1000(IMAGE_DECLARATION(src0),
IMAGE_DECLARATION(src1),
-#if defined(ADD_VEC_C)
- VECTOR_DECLARATION(src2),
-#endif /* defined(ADD_VEC_C) */
+#if defined(BETA)
+ IMAGE_DECLARATION(src2),
+#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint src0_stride_z,
uint src1_stride_z,
+#if defined(BETA)
+ uint src2_stride_z,
+#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_INPUT_AS_3D)
,
@@ -4566,20 +4605,15 @@ __kernel void gemm_mm_floating_point_f32_bifrost_1000(IMAGE_DECLARATION(src0),
#endif // defined(MATRIX_B_DEPTH)
// Initialize accumulators
- float acc00 = 0.0f;
- float acc01 = 0.0f;
-
+ float2 acc0 = 0.0f;
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- float acc10 = 0.0f;
- float acc11 = 0.0f;
+ float2 acc1 = 0.0f;
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- float acc20 = 0.0f;
- float acc21 = 0.0f;
+ float2 acc2 = 0.0f;
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- float acc30 = 0.0f;
- float acc31 = 0.0f;
+ float2 acc3 = 0.0f;
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
// A and B src indices get incremented at the same time.
@@ -4613,95 +4647,95 @@ __kernel void gemm_mm_floating_point_f32_bifrost_1000(IMAGE_DECLARATION(src0),
src_addr.s1 += src1_stride_y;
// Multiply and accumulate
- acc00 = fma(a0.s0, b0.s0, acc00);
- acc00 = fma(a0.s1, b1.s0, acc00);
- acc00 = fma(a0.s2, b2.s0, acc00);
- acc00 = fma(a0.s3, b3.s0, acc00);
- acc00 = fma(a0.s4, b4.s0, acc00);
- acc00 = fma(a0.s5, b5.s0, acc00);
- acc00 = fma(a0.s6, b6.s0, acc00);
- acc00 = fma(a0.s7, b7.s0, acc00);
-
- acc01 = fma(a0.s0, b0.s1, acc01);
- acc01 = fma(a0.s1, b1.s1, acc01);
- acc01 = fma(a0.s2, b2.s1, acc01);
- acc01 = fma(a0.s3, b3.s1, acc01);
- acc01 = fma(a0.s4, b4.s1, acc01);
- acc01 = fma(a0.s5, b5.s1, acc01);
- acc01 = fma(a0.s6, b6.s1, acc01);
- acc01 = fma(a0.s7, b7.s1, acc01);
+ acc0.s0 = fma(a0.s0, b0.s0, acc0.s0);
+ acc0.s0 = fma(a0.s1, b1.s0, acc0.s0);
+ acc0.s0 = fma(a0.s2, b2.s0, acc0.s0);
+ acc0.s0 = fma(a0.s3, b3.s0, acc0.s0);
+ acc0.s0 = fma(a0.s4, b4.s0, acc0.s0);
+ acc0.s0 = fma(a0.s5, b5.s0, acc0.s0);
+ acc0.s0 = fma(a0.s6, b6.s0, acc0.s0);
+ acc0.s0 = fma(a0.s7, b7.s0, acc0.s0);
+
+ acc0.s1 = fma(a0.s0, b0.s1, acc0.s1);
+ acc0.s1 = fma(a0.s1, b1.s1, acc0.s1);
+ acc0.s1 = fma(a0.s2, b2.s1, acc0.s1);
+ acc0.s1 = fma(a0.s3, b3.s1, acc0.s1);
+ acc0.s1 = fma(a0.s4, b4.s1, acc0.s1);
+ acc0.s1 = fma(a0.s5, b5.s1, acc0.s1);
+ acc0.s1 = fma(a0.s6, b6.s1, acc0.s1);
+ acc0.s1 = fma(a0.s7, b7.s1, acc0.s1);
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if defined(REINTERPRET_INPUT_AS_3D)
a0 = vload8(0, (__global float *)(src0_ptr + src_addr.s0 + 1 * src0_stride_y + zin.s1));
#else // defined(REINTERPRET_INPUT_AS_3D)
- a0 = vload8(0, (__global float *)(src0_ptr + src_addr.s0 + 1 * src0_stride_y));
+ a0 = vload8(0, (__global float *)(src0_ptr + src_addr.s0 + 1 * src0_stride_y));
#endif // defined(REINTERPRET_INPUT_AS_3D)
- acc10 = fma(a0.s0, b0.s0, acc10);
- acc10 = fma(a0.s1, b1.s0, acc10);
- acc10 = fma(a0.s2, b2.s0, acc10);
- acc10 = fma(a0.s3, b3.s0, acc10);
- acc10 = fma(a0.s4, b4.s0, acc10);
- acc10 = fma(a0.s5, b5.s0, acc10);
- acc10 = fma(a0.s6, b6.s0, acc10);
- acc10 = fma(a0.s7, b7.s0, acc10);
-
- acc11 = fma(a0.s0, b0.s1, acc11);
- acc11 = fma(a0.s1, b1.s1, acc11);
- acc11 = fma(a0.s2, b2.s1, acc11);
- acc11 = fma(a0.s3, b3.s1, acc11);
- acc11 = fma(a0.s4, b4.s1, acc11);
- acc11 = fma(a0.s5, b5.s1, acc11);
- acc11 = fma(a0.s6, b6.s1, acc11);
- acc11 = fma(a0.s7, b7.s1, acc11);
+ acc1.s0 = fma(a0.s0, b0.s0, acc1.s0);
+ acc1.s0 = fma(a0.s1, b1.s0, acc1.s0);
+ acc1.s0 = fma(a0.s2, b2.s0, acc1.s0);
+ acc1.s0 = fma(a0.s3, b3.s0, acc1.s0);
+ acc1.s0 = fma(a0.s4, b4.s0, acc1.s0);
+ acc1.s0 = fma(a0.s5, b5.s0, acc1.s0);
+ acc1.s0 = fma(a0.s6, b6.s0, acc1.s0);
+ acc1.s0 = fma(a0.s7, b7.s0, acc1.s0);
+
+ acc1.s1 = fma(a0.s0, b0.s1, acc1.s1);
+ acc1.s1 = fma(a0.s1, b1.s1, acc1.s1);
+ acc1.s1 = fma(a0.s2, b2.s1, acc1.s1);
+ acc1.s1 = fma(a0.s3, b3.s1, acc1.s1);
+ acc1.s1 = fma(a0.s4, b4.s1, acc1.s1);
+ acc1.s1 = fma(a0.s5, b5.s1, acc1.s1);
+ acc1.s1 = fma(a0.s6, b6.s1, acc1.s1);
+ acc1.s1 = fma(a0.s7, b7.s1, acc1.s1);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if defined(REINTERPRET_INPUT_AS_3D)
a0 = vload8(0, (__global float *)(src0_ptr + src_addr.s0 + 2 * src0_stride_y + zin.s2));
#else // defined(REINTERPRET_INPUT_AS_3D)
- a0 = vload8(0, (__global float *)(src0_ptr + src_addr.s0 + 2 * src0_stride_y));
+ a0 = vload8(0, (__global float *)(src0_ptr + src_addr.s0 + 2 * src0_stride_y));
#endif // defined(REINTERPRET_INPUT_AS_3D)
- acc20 = fma(a0.s0, b0.s0, acc20);
- acc20 = fma(a0.s1, b1.s0, acc20);
- acc20 = fma(a0.s2, b2.s0, acc20);
- acc20 = fma(a0.s3, b3.s0, acc20);
- acc20 = fma(a0.s4, b4.s0, acc20);
- acc20 = fma(a0.s5, b5.s0, acc20);
- acc20 = fma(a0.s6, b6.s0, acc20);
- acc20 = fma(a0.s7, b7.s0, acc20);
-
- acc21 = fma(a0.s0, b0.s1, acc21);
- acc21 = fma(a0.s1, b1.s1, acc21);
- acc21 = fma(a0.s2, b2.s1, acc21);
- acc21 = fma(a0.s3, b3.s1, acc21);
- acc21 = fma(a0.s4, b4.s1, acc21);
- acc21 = fma(a0.s5, b5.s1, acc21);
- acc21 = fma(a0.s6, b6.s1, acc21);
- acc21 = fma(a0.s7, b7.s1, acc21);
+ acc2.s0 = fma(a0.s0, b0.s0, acc2.s0);
+ acc2.s0 = fma(a0.s1, b1.s0, acc2.s0);
+ acc2.s0 = fma(a0.s2, b2.s0, acc2.s0);
+ acc2.s0 = fma(a0.s3, b3.s0, acc2.s0);
+ acc2.s0 = fma(a0.s4, b4.s0, acc2.s0);
+ acc2.s0 = fma(a0.s5, b5.s0, acc2.s0);
+ acc2.s0 = fma(a0.s6, b6.s0, acc2.s0);
+ acc2.s0 = fma(a0.s7, b7.s0, acc2.s0);
+
+ acc2.s1 = fma(a0.s0, b0.s1, acc2.s1);
+ acc2.s1 = fma(a0.s1, b1.s1, acc2.s1);
+ acc2.s1 = fma(a0.s2, b2.s1, acc2.s1);
+ acc2.s1 = fma(a0.s3, b3.s1, acc2.s1);
+ acc2.s1 = fma(a0.s4, b4.s1, acc2.s1);
+ acc2.s1 = fma(a0.s5, b5.s1, acc2.s1);
+ acc2.s1 = fma(a0.s6, b6.s1, acc2.s1);
+ acc2.s1 = fma(a0.s7, b7.s1, acc2.s1);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
#if defined(REINTERPRET_INPUT_AS_3D)
a0 = vload8(0, (__global float *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y + zin.s3));
#else // defined(REINTERPRET_INPUT_AS_3D)
- a0 = vload8(0, (__global float *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y));
+ a0 = vload8(0, (__global float *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y));
#endif // defined(REINTERPRET_INPUT_AS_3D)
- acc30 = fma(a0.s0, b0.s0, acc30);
- acc30 = fma(a0.s1, b1.s0, acc30);
- acc30 = fma(a0.s2, b2.s0, acc30);
- acc30 = fma(a0.s3, b3.s0, acc30);
- acc30 = fma(a0.s4, b4.s0, acc30);
- acc30 = fma(a0.s5, b5.s0, acc30);
- acc30 = fma(a0.s6, b6.s0, acc30);
- acc30 = fma(a0.s7, b7.s0, acc30);
-
- acc31 = fma(a0.s0, b0.s1, acc31);
- acc31 = fma(a0.s1, b1.s1, acc31);
- acc31 = fma(a0.s2, b2.s1, acc31);
- acc31 = fma(a0.s3, b3.s1, acc31);
- acc31 = fma(a0.s4, b4.s1, acc31);
- acc31 = fma(a0.s5, b5.s1, acc31);
- acc31 = fma(a0.s6, b6.s1, acc31);
- acc31 = fma(a0.s7, b7.s1, acc31);
+ acc3.s0 = fma(a0.s0, b0.s0, acc3.s0);
+ acc3.s0 = fma(a0.s1, b1.s0, acc3.s0);
+ acc3.s0 = fma(a0.s2, b2.s0, acc3.s0);
+ acc3.s0 = fma(a0.s3, b3.s0, acc3.s0);
+ acc3.s0 = fma(a0.s4, b4.s0, acc3.s0);
+ acc3.s0 = fma(a0.s5, b5.s0, acc3.s0);
+ acc3.s0 = fma(a0.s6, b6.s0, acc3.s0);
+ acc3.s0 = fma(a0.s7, b7.s0, acc3.s0);
+
+ acc3.s1 = fma(a0.s0, b0.s1, acc3.s1);
+ acc3.s1 = fma(a0.s1, b1.s1, acc3.s1);
+ acc3.s1 = fma(a0.s2, b2.s1, acc3.s1);
+ acc3.s1 = fma(a0.s3, b3.s1, acc3.s1);
+ acc3.s1 = fma(a0.s4, b4.s1, acc3.s1);
+ acc3.s1 = fma(a0.s5, b5.s1, acc3.s1);
+ acc3.s1 = fma(a0.s6, b6.s1, acc3.s1);
+ acc3.s1 = fma(a0.s7, b7.s1, acc3.s1);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
src_addr.s0 += sizeof(float) * 8;
@@ -4740,42 +4774,24 @@ __kernel void gemm_mm_floating_point_f32_bifrost_1000(IMAGE_DECLARATION(src0),
src_addr.s1 += src1_stride_y;
// Multiply and accumulate
- acc00 = fma(a0, b0.s0, acc00);
- acc01 = fma(a0, b0.s1, acc01);
+ acc0.s0 = fma(a0, b0.s0, acc0.s0);
+ acc0.s1 = fma(a0, b0.s1, acc0.s1);
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- acc10 = fma(a1, b0.s0, acc10);
- acc11 = fma(a1, b0.s1, acc11);
+ acc1.s0 = fma(a1, b0.s0, acc1.s0);
+ acc1.s1 = fma(a1, b0.s1, acc1.s1);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- acc20 = fma(a2, b0.s0, acc20);
- acc21 = fma(a2, b0.s1, acc21);
+ acc2.s0 = fma(a2, b0.s0, acc2.s0);
+ acc2.s1 = fma(a2, b0.s1, acc2.s1);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- acc30 = fma(a3, b0.s0, acc30);
- acc31 = fma(a3, b0.s1, acc31);
+ acc3.s0 = fma(a3, b0.s0, acc3.s0);
+ acc3.s1 = fma(a3, b0.s1, acc3.s1);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
src_addr.s0 += sizeof(float);
}
- // Multiply by the weight of matrix-matrix product and store the result
-#if defined(ALPHA)
- acc00 = acc00 * ALPHA;
- acc01 = acc01 * ALPHA;
-#endif // defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 && defined(ALPHA)
- acc10 = acc10 * ALPHA;
- acc11 = acc11 * ALPHA;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 && defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 && defined(ALPHA)
- acc20 = acc20 * ALPHA;
- acc21 = acc21 * ALPHA;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 && defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 && defined(ALPHA)
- acc30 = acc30 * ALPHA;
- acc31 = acc31 * ALPHA;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 && defined(ALPHA)
-
int z = get_global_id(2);
// Compute destination address
@@ -4784,27 +4800,10 @@ __kernel void gemm_mm_floating_point_f32_bifrost_1000(IMAGE_DECLARATION(src0),
// Compute dst address
__global uchar *dst_addr = offset(&dst, 0, 0);
-#if defined(ADD_VEC_C)
- __global float *src2_addr = (__global float *)(src2_ptr + src2_offset_first_element_in_bytes + get_global_id(0) * src2_step_x);
- float2 c0 = vload2(0, src2_addr);
-
- acc00 += c0.s0;
- acc01 += c0.s1;
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- acc10 += c0.s0;
- acc11 += c0.s1;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- acc20 += c0.s0;
- acc21 += c0.s1;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- acc30 += c0.s0;
- acc31 += c0.s1;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-#endif /* defined(ADD_VEC_C) */
+ uint4 zout = 0;
#if defined(REINTERPRET_OUTPUT_AS_3D)
+
// Since we store a 2D output tile in a 3D tensor, we need to check when the plane changes across the z dimension
// in order to take into account the presence of possible cross plane paddings
//
@@ -4821,8 +4820,8 @@ __kernel void gemm_mm_floating_point_f32_bifrost_1000(IMAGE_DECLARATION(src0),
// |__________________|
// The plane (zout) is calculated dividing M (get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y) by HEIGHT_GEMM3D
- uint4 zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y)) / (uint4)HEIGHT_GEMM3D;
- zout = min(DEPTH_GEMM3D - 1, zout);
+ zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y)) / (uint4)HEIGHT_GEMM3D;
+ zout = min(DEPTH_GEMM3D - 1, zout);
// Add offset due to the cross plane paddings
zout *= (dst_cross_plane_pad * dst_stride_y);
@@ -4830,50 +4829,78 @@ __kernel void gemm_mm_floating_point_f32_bifrost_1000(IMAGE_DECLARATION(src0),
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
-
- // Store the output block
- vstore2((float2)(acc00, acc01), 0, (__global float *)(dst_addr + 0 * dst_stride_y + zout.s0));
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- vstore2((float2)(acc10, acc11), 0, (__global float *)(dst_addr + 1 * dst_stride_y + zout.s1));
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- vstore2((float2)(acc20, acc21), 0, (__global float *)(dst_addr + 2 * dst_stride_y + zout.s2));
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- vstore2((float2)(acc30, acc31), 0, (__global float *)(dst_addr + 3 * dst_stride_y + zout.s3));
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-
-#else // defined(REINTERPRET_OUTPUT_AS_3D)
+#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
+#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+
+ // Multiply by the weight of matrix-matrix product and store the result
+#if defined(ALPHA)
+ SCALE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, float, acc, ALPHA);
+#endif // defined(ALPHA)
+
+ // Add beta*bias
+#if defined(BETA)
+ REPEAT_VAR_INIT_TO_CONST(NUM_ELEMS_PROCESSED_PER_THREAD_Y, uint, zero, 0);
+
+#if defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)2 * sizeof(float));
+
+ LOAD_BLOCK(1, 2, float, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(1, float, bias, BETA);
+#endif // UNIT_BIAS
+
+ // acc = acc + bias[broadcasted]
+ ADD_BLOCK_BROADCAST(NUM_ELEMS_PROCESSED_PER_THREAD_Y, acc, bias0);
+
+#else // defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)2 * sizeof(float)) + (get_global_id(1) *
+ (uint)NUM_ELEMS_PROCESSED_PER_THREAD_Y * src2_stride_y) + get_global_id(2) * src2_stride_z;
+
+ LOAD_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, 2, float, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, float, bias, BETA);
+#endif // UNIT_BIAS
+
+ // acc = acc + bias
+ ADD_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, acc, bias);
+
+#endif // defined(BROADCAST_BIAS)
+#endif // defined(BETA)
+
+#if defined(ACTIVATION_TYPE)
+ ACTIVATION_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, ACTIVATION_TYPE, float, acc, A_VAL, B_VAL);
+#endif // defined(ACTIVATION_TYPE)
// Store the output block
- vstore2((float2)(acc00, acc01), 0, (__global float *)(dst_addr + 0 * dst_stride_y));
+ vstore2(acc0, 0, (__global float *)(dst_addr + 0 * dst_stride_y + zout.s0));
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- vstore2((float2)(acc10, acc11), 0, (__global float *)(dst_addr + 1 * dst_stride_y));
+ vstore2(acc1, 0, (__global float *)(dst_addr + 1 * dst_stride_y + zout.s1));
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- vstore2((float2)(acc20, acc21), 0, (__global float *)(dst_addr + 2 * dst_stride_y));
+ vstore2(acc2, 0, (__global float *)(dst_addr + 2 * dst_stride_y + zout.s2));
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- vstore2((float2)(acc30, acc31), 0, (__global float *)(dst_addr + 3 * dst_stride_y));
+ vstore2(acc3, 0, (__global float *)(dst_addr + 3 * dst_stride_y + zout.s3));
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-#endif // defined(REINTERPRET_OUTPUT_AS_3D)
}
#if defined(ARM_COMPUTE_OPENCL_FP16_ENABLED)
/** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not beed reshaped
*
- * Moreover, it can add a vector (src2) if the ADD_VEC_C parameter is passed at compile time.
- *
* @note This OpenCL kernel works with the 16-bit floating point data type (half) and accumulating the result in a 32 floating point variable.
* @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y.
* This kernel optimally uses -DNUM_ELEMS_PROCESSED_PER_THREAD_X=4.
* @note The number of matrix A columns must be passed at compile time using -DCOLS_A.
* @note The optional value of scalar alpha is passed at compile time using -DALPHA=alpha
- * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
- * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (e.g. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (e.g. a = [K, M, 16, Batches], b = [N, K, 16])
*
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
@@ -4881,8 +4908,6 @@ __kernel void gemm_mm_floating_point_f32_bifrost_1000(IMAGE_DECLARATION(src0),
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns matrix A NOT reshaped
*
- * @note In case a 3rd input (src2) needs to be added, the ADD_VEC_C parameter has to be passed at compile time as -DADD_VEC_C
- *
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
@@ -4895,10 +4920,12 @@ __kernel void gemm_mm_floating_point_f32_bifrost_1000(IMAGE_DECLARATION(src0),
* @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes)
* @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix
- * @param[in] src2_ptr (Optional) Pointer to the source matrix. Supported data types: same as @p src0_ptr
- * @param[in] src2_stride_x (Optional) Stride of the source vector in X dimension (in bytes)
- * @param[in] src2_step_x (Optional) src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the source matrix
+ * @param[in] src2_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
+ * @param[in] src2_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
+ * @param[in] src2_step_x (Optional) src2_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src2_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
+ * @param[in] src2_step_y (Optional) src2_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src0_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes)
@@ -4907,18 +4934,22 @@ __kernel void gemm_mm_floating_point_f32_bifrost_1000(IMAGE_DECLARATION(src0),
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] src0_stride_z Stride of the source matrix in Z dimension (in bytes)
* @param[in] src1_stride_z Stride of the source matrix in Z dimension (in bytes)
+ * @param[in] src2_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] src_cross_plane_pad (Optional) Bottom paddings in unit of elements for the input tensor (only if defined REINTERPRET_INPUT_AS_3D)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
*/
__kernel void gemm_mm_floating_point_f16_bifrost_acc32(IMAGE_DECLARATION(src0),
IMAGE_DECLARATION(src1),
-#if defined(ADD_VEC_C)
- VECTOR_DECLARATION(src2),
-#endif /* defined(ADD_VEC_C) */
+#if defined(BETA)
+ IMAGE_DECLARATION(src2),
+#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint src0_stride_z,
uint src1_stride_z,
+#if defined(BETA)
+ uint src2_stride_z,
+#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_INPUT_AS_3D)
,
@@ -5117,56 +5148,6 @@ __kernel void gemm_mm_floating_point_f16_bifrost_acc32(IMAGE_DECLARATION(src0),
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
}
- // Multiply by the weight of matrix-matrix product and store the result
-#if defined(ALPHA)
- half8 hacc0 = convert_half8(acc0) * (half8)ALPHA;
-#else //defined(ALPHA)
- half8 hacc0 = convert_half8(acc0);
-#endif // defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
-#if defined(ALPHA)
- half8 hacc1 = convert_half8(acc1) * (half8)ALPHA;
-#else //defined(ALPHA)
- half8 hacc1 = convert_half8(acc1);
-#endif //defined(ALPHA)
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y
-
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
-#if defined(ALPHA)
- half8 hacc2 = convert_half8(acc2) * (half8)ALPHA;
-#else //defined(ALPHA)
- half8 hacc2 = convert_half8(acc2);
-#endif //defined(ALPHA)
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
-
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-#if defined(ALPHA)
- half8 hacc3 = convert_half8(acc3) * (half8)ALPHA;
-#else //defined(ALPHA)
- half8 hacc3 = convert_half8(acc3);
-#endif // defined(ALPHA)
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-
-#if defined(ADD_VEC_C)
- // *INDENT-OFF*
- // clang-format off
- __global half *src2_addr = (__global half *)(src2_ptr + src2_offset_first_element_in_bytes + get_global_id(0) * src2_step_x);
- half8 c0 = vload8(0, src2_addr);
- // clang-format on
- // *INDENT-ON*
-
- hacc0 += c0;
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- hacc1 += c0;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- hacc2 += c0;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- hacc3 += c0;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-#endif /* defined(ADD_VEC_C) */
-
int z = get_global_id(2);
// Compute destination address
@@ -5175,7 +5156,10 @@ __kernel void gemm_mm_floating_point_f16_bifrost_acc32(IMAGE_DECLARATION(src0),
// Compute dst address
__global uchar *dst_addr = offset(&dst, 0, 0);
+ uint4 zout = 0;
+
#if defined(REINTERPRET_OUTPUT_AS_3D)
+
// Since we store a 2D output tile in a 3D tensor, we need to check when the plane changes across the z dimension
// in order to take into account the presence of possible cross plane paddings
//
@@ -5192,8 +5176,8 @@ __kernel void gemm_mm_floating_point_f16_bifrost_acc32(IMAGE_DECLARATION(src0),
// |__________________|
// The plane (zout) is calculated dividing M (get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y) by HEIGHT_GEMM3D
- uint4 zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y)) / (uint4)HEIGHT_GEMM3D;
- zout = min(DEPTH_GEMM3D - 1, zout);
+ zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y)) / (uint4)HEIGHT_GEMM3D;
+ zout = min(DEPTH_GEMM3D - 1, zout);
// Add offset due to the cross plane paddings
zout *= (dst_cross_plane_pad * dst_stride_y);
@@ -5201,38 +5185,91 @@ __kernel void gemm_mm_floating_point_f16_bifrost_acc32(IMAGE_DECLARATION(src0),
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
- // Store the output block
- STORE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, 8, half, hacc, dst_addr, dst_stride_y, zout.s);
-#else // defined(REINTERPRET_OUTPUT_AS_3D)
+#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
+#endif // defined(REINTERPRET_OUTPUT_AS_3D)
- // Store the output block
- vstore8(hacc0, 0, (__global half *)(dst_addr + 0 * dst_stride_y));
+ // Multiply by the weight of matrix-matrix product and store the result
+#if defined(ALPHA)
+ SCALE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, float, acc, ALPHA);
+#endif // defined(ALPHA)
+
+#if defined(BETA)
+ REPEAT_VAR_INIT_TO_CONST(NUM_ELEMS_PROCESSED_PER_THREAD_Y, uint, zero, 0);
+
+#if defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)8 * sizeof(half));
+
+ LOAD_BLOCK(1, 8, half, bias, src2_addr, 0, src2_stride_y, zero);
+
+ float8 bias_f0 = convert_float8(bias0);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(1, float, bias_f, BETA);
+#endif // UNIT_BIAS
+
+ // acc = acc + bias[broadcasted]
+ ADD_BLOCK_BROADCAST(NUM_ELEMS_PROCESSED_PER_THREAD_Y, acc, bias_f0);
+
+#else // defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)8 * sizeof(half)) + (get_global_id(1) *
+ (uint)NUM_ELEMS_PROCESSED_PER_THREAD_Y * src2_stride_y) + get_global_id(2) * src2_stride_z;
+
+ LOAD_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, 8, half, bias, src2_addr, 0, src2_stride_y, zero);
+
+ float8 bias_f0 = convert_float8(bias0);
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- vstore8(hacc1, 0, (__global half *)(dst_addr + 1 * dst_stride_y));
+ float8 bias_f1 = convert_float8(bias1);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- vstore8(hacc2, 0, (__global half *)(dst_addr + 2 * dst_stride_y));
+ float8 bias_f2 = convert_float8(bias2);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- vstore8(hacc3, 0, (__global half *)(dst_addr + 3 * dst_stride_y));
+ float8 bias_f3 = convert_float8(bias3);
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-#endif // REINTERPRET_OUTPUT_AS_3D
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, float, bias_f, BETA);
+#endif // UNIT_BIAS
+
+ // acc = acc + bias
+ ADD_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, acc, bias_f);
+
+#endif // defined(BROADCAST_BIAS)
+#endif // defined(BETA)
+
+ half8 acc_h0 = convert_half8(acc0);
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ half8 acc_h1 = convert_half8(acc1);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ half8 acc_h2 = convert_half8(acc2);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ half8 acc_h3 = convert_half8(acc3);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+
+#if defined(ACTIVATION_TYPE)
+ ACTIVATION_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, ACTIVATION_TYPE, half, acc_h, A_VAL, B_VAL);
+#endif // defined(ACTIVATION_TYPE)
+
+ // Store the output block
+ STORE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, 8, half, acc_h, dst_addr, dst_stride_y, zout.s);
}
/** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not beed reshaped
*
- * Moreover, it can add a vector (src2) if the ADD_VEC_C parameter is passed at compile time.
- *
* @note This OpenCL kernel works with the 16-bit floating point data type (half) and uses the fma units.
* @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y.
* This kernel optimally uses -DNUM_ELEMS_PROCESSED_PER_THREAD_X=4.
* @note The number of matrix A columns must be passed at compile time using -DCOLS_A.
* @note The optional value of scalar alpha is passed at compile time using -DALPHA=alpha
- * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
- * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (e.g. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (e.g. a = [K, M, 16, Batches], b = [N, K, 16])
*
+ * @note If the activation type were passed at compile time through -DACTIVATION_TYPE (e.g. -DACTIVATION_TYPE=RELU), A, B variables, required by some activation functions, should be passed at compile time as well using -DA_VAL= and -DB_VAL= respectively.
+ * The activation function is performed after the bias addition
* @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
* -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
* -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
@@ -5240,8 +5277,6 @@ __kernel void gemm_mm_floating_point_f16_bifrost_acc32(IMAGE_DECLARATION(src0),
* -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
* (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns matrix A NOT reshaped
*
- * @note In case a 3rd input (src2) needs to be added, the ADD_VEC_C parameter has to be passed at compile time as -DADD_VEC_C
- *
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
@@ -5254,10 +5289,12 @@ __kernel void gemm_mm_floating_point_f16_bifrost_acc32(IMAGE_DECLARATION(src0),
* @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes)
* @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix
- * @param[in] src2_ptr (Optional) Pointer to the source matrix. Supported data types: same as @p src0_ptr
- * @param[in] src2_stride_x (Optional) Stride of the source vector in X dimension (in bytes)
- * @param[in] src2_step_x (Optional) src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the source matrix
+ * @param[in] src2_ptr (Optional) Pointer to the bias matrix. Supported data type: same as @p lhs_ptr
+ * @param[in] src2_stride_x (Optional) Stride of the bias matrix in X dimension (in bytes)
+ * @param[in] src2_step_x (Optional) src2_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src2_stride_y (Optional) Stride of the bias matrix in Y dimension (in bytes)
+ * @param[in] src2_step_y (Optional) src2_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src2_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
* @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src0_ptr
* @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
* @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes)
@@ -5266,18 +5303,22 @@ __kernel void gemm_mm_floating_point_f16_bifrost_acc32(IMAGE_DECLARATION(src0),
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
* @param[in] src0_stride_z Stride of the source matrix in Z dimension (in bytes)
* @param[in] src1_stride_z Stride of the source matrix in Z dimension (in bytes)
+ * @param[in] src2_stride_z (Optional) Stride of the bias matrix in Z dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] src_cross_plane_pad (Optional) Bottom paddings in unit of elements for the input tensor (only if defined REINTERPRET_INPUT_AS_3D)
* @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
*/
__kernel void gemm_mm_floating_point_f16_bifrost(IMAGE_DECLARATION(src0),
IMAGE_DECLARATION(src1),
-#if defined(ADD_VEC_C)
- VECTOR_DECLARATION(src2),
-#endif /* defined(ADD_VEC_C) */
+#if defined(BETA)
+ IMAGE_DECLARATION(src2),
+#endif // defined(BETA)
IMAGE_DECLARATION(dst),
uint src0_stride_z,
uint src1_stride_z,
+#if defined(BETA)
+ uint src2_stride_z,
+#endif //defined(BETA)
uint dst_stride_z
#if defined(REINTERPRET_INPUT_AS_3D)
,
@@ -5476,40 +5517,6 @@ __kernel void gemm_mm_floating_point_f16_bifrost(IMAGE_DECLARATION(src0),
#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
}
- // Multiply by the weight of matrix-matrix product and store the result
-#if defined(ALPHA)
- acc0 = acc0 * (half8)ALPHA;
-#endif // defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 && defined(ALPHA)
- acc1 = acc1 * (half8)ALPHA;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 && defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 && defined(ALPHA)
- acc2 = acc2 * (half8)ALPHA;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 && defined(ALPHA)
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 && defined(ALPHA)
- acc3 = acc3 * (half8)ALPHA;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 && defined(ALPHA)
-
-#if defined(ADD_VEC_C)
- // *INDENT-OFF*
- // clang-format off
- __global half *src2_addr = (__global half *)(src2_ptr + src2_offset_first_element_in_bytes + get_global_id(0) * src2_step_x);
- half8 c0 = vload8(0, src2_addr);
- // clang-format on
- // *INDENT-ON*
-
- acc0 += c0;
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- acc1 += c0;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- acc2 += c0;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- acc3 += c0;
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-#endif /* defined(ADD_VEC_C) */
-
int z = get_global_id(2);
// Compute destination address
@@ -5518,7 +5525,10 @@ __kernel void gemm_mm_floating_point_f16_bifrost(IMAGE_DECLARATION(src0),
// Compute dst address
__global uchar *dst_addr = offset(&dst, 0, 0);
+ uint4 zout = 0;
+
#if defined(REINTERPRET_OUTPUT_AS_3D)
+
// Since we store a 2D output tile in a 3D tensor, we need to check when the plane changes across the z dimension
// in order to take into account the presence of possible cross plane paddings
//
@@ -5535,8 +5545,8 @@ __kernel void gemm_mm_floating_point_f16_bifrost(IMAGE_DECLARATION(src0),
// |__________________|
// The plane (zout) is calculated dividing M (get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y) by HEIGHT_GEMM3D
- uint4 zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y)) / (uint4)HEIGHT_GEMM3D;
- zout = min(DEPTH_GEMM3D - 1, zout);
+ zout = ((uint4)(0, 1, 2, 3) + (uint4)(get_global_id(1) * NUM_ELEMS_PROCESSED_PER_THREAD_Y)) / (uint4)HEIGHT_GEMM3D;
+ zout = min(DEPTH_GEMM3D - 1, zout);
// Add offset due to the cross plane paddings
zout *= (dst_cross_plane_pad * dst_stride_y);
@@ -5544,25 +5554,54 @@ __kernel void gemm_mm_floating_point_f16_bifrost(IMAGE_DECLARATION(src0),
// Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
// multiply dst_stride_z by DEPTH_GEMM3D
dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
-
- // Store the output block
- STORE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, 8, half, acc, dst_addr, dst_stride_y, zout.s);
-#else // defined(REINTERPRET_OUTPUT_AS_3D)
+#else // defined(REINTERPRET_OUTPUT_AS_3D)
// Add offset for batched GEMM
dst_addr += z * dst_stride_z;
+#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+
+ // Multiply by the weight of matrix-matrix product and store the result
+#if defined(ALPHA)
+ SCALE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, half, acc, ALPHA);
+#endif // defined(ALPHA)
+
+ // Add beta*bias
+#if defined(BETA)
+ REPEAT_VAR_INIT_TO_CONST(NUM_ELEMS_PROCESSED_PER_THREAD_Y, uint, zero, 0);
+
+#if defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)8 * sizeof(half));
+
+ LOAD_BLOCK(1, 8, half, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(1, half, bias, BETA);
+#endif // UNIT_BIAS
+
+ // acc = acc + bias[broadcasted]
+ ADD_BLOCK_BROADCAST(NUM_ELEMS_PROCESSED_PER_THREAD_Y, acc, bias0);
+
+#else // defined(BROADCAST_BIAS)
+ __global uchar *src2_addr = src2_ptr + src2_offset_first_element_in_bytes + (get_global_id(0) * (uint)8 * sizeof(half)) + (get_global_id(1) *
+ (uint)NUM_ELEMS_PROCESSED_PER_THREAD_Y * src2_stride_y) + get_global_id(2) * src2_stride_z;
+
+ LOAD_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, 8, half, bias, src2_addr, 0, src2_stride_y, zero);
+
+#ifndef UNIT_BETA
+ SCALE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, half, bias, BETA);
+#endif // UNIT_BIAS
+
+ // acc = acc + bias
+ ADD_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, acc, bias);
+
+#endif // defined(BROADCAST_BIAS)
+#endif // defined(BETA)
+
+#if defined(ACTIVATION_TYPE)
+ ACTIVATION_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, ACTIVATION_TYPE, half, acc, A_VAL, B_VAL);
+#endif // defined(ACTIVATION_TYPE)
// Store the output block
- vstore8(acc0, 0, (__global half *)(dst_addr + 0 * dst_stride_y));
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
- vstore8(acc1, 0, (__global half *)(dst_addr + 1 * dst_stride_y));
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
- vstore8(acc2, 0, (__global half *)(dst_addr + 2 * dst_stride_y));
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
-#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- vstore8(acc3, 0, (__global half *)(dst_addr + 3 * dst_stride_y));
-#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
-#endif // REINTERPRET_OUTPUT_AS_3D
+ STORE_BLOCK(NUM_ELEMS_PROCESSED_PER_THREAD_Y, 8, half, acc, dst_addr, dst_stride_y, zout.s);
}
#endif // defined(ARM_COMPUTE_OPENCL_FP16_ENABLED)
@@ -5746,7 +5785,7 @@ __kernel void gemm_accumulate_biases(
Image accum = CONVERT_TO_IMAGE_STRUCT(accum);
Vector biases = CONVERT_TO_VECTOR_STRUCT(biases);
- // Vector size, i.e. number of vector elements.
+ // Vector size, e.g. number of vector elements.
VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE)
accum_value = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)accum.ptr);
VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE)
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
index b3ea309c93..e793c65059 100644
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
@@ -62,27 +62,34 @@ inline Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *i
ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_interleaved_transposed && reshape_info.reinterpret_input_as_3d(), "The input tensor cannot be reinterpreted as 3D if is_interleaved_transposed is true");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->num_dimensions() > 2 && reshape_info.reinterpret_input_as_3d(), "The input1 tensor cannot have more than 2 dimensions if input0 has to be reinterpreted as 3D");
- const bool is_beta_one = std::abs(1.0f - beta) < 0.00001f;
- const bool has_vec_c = input2 != nullptr && beta != 0.f;
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(has_vec_c && !is_beta_one, "Adding input2 is only supported for beta equal to 1");
-
if(!is_interleaved_transposed)
{
ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(0) != input1->dimension(1));
- if(has_vec_c)
+ if(input2 != nullptr && !(helpers::float_ops::is_zero(beta)))
{
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input2);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(input2->num_dimensions() > 1, "input2 must be a 1D tensor");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(input2->dimension(0) != input1->dimension(0), "Length of Vector C must match the number of columns of matrix B");
+ const unsigned int m = reshape_info.reinterpret_input_as_3d() ? input0->dimension(1) * input0->dimension(2) : input0->dimension(1);
+ const unsigned int n = input1->dimension(0);
+ const unsigned int input2_dim0 = input2->dimension(0);
+ const unsigned int input2_dim1 = input2->dimension(1);
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input2, input1);
+ if(reshape_info.broadcast_bias())
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG((input2_dim1 != 1 || input2_dim0 != n), "Incorrect dimension of bias matrix which is to be broadcasted");
+ }
+ else
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG((input2_dim0 != n || input2_dim1 != m), "Incorrect dimension of bias matrix");
+ }
}
}
else
{
GEMMRHSMatrixInfo rhs_info;
GEMMLHSMatrixInfo lhs_info;
- const int m = reshape_info.m();
- const int n = reshape_info.n();
+ const auto m = static_cast<unsigned int>(reshape_info.m());
+ const auto n = static_cast<unsigned int>(reshape_info.n());
const int k = reshape_info.k();
const int mult_transpose1xW_width = reshape_info.mult_transpose1xW_width();
const int mult_interleave4x4_height = reshape_info.mult_interleave4x4_height();
@@ -114,10 +121,20 @@ inline Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *i
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input0, &tensor_info_reshaped0);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, &tensor_info_reshaped1);
- if(has_vec_c)
+ if(input2 != nullptr && !(helpers::float_ops::is_zero(beta)))
{
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input2);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(input2->num_dimensions() > 1, "input2 must be a 1D tensor");
+ const unsigned int input2_dim0 = input2->dimension(0);
+ const unsigned int input2_dim1 = input2->dimension(1);
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input2, input1);
+ if(reshape_info.broadcast_bias())
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG((input2_dim1 != 1 || input2_dim0 != n), "Incorrect dimension of bias matrix which is to be broadcasted");
+ }
+ else
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG((input2_dim0 != n || input2_dim1 != m), "Incorrect dimension of bias matrix");
+ }
}
}
@@ -145,7 +162,6 @@ inline std::pair<Status, Window> validate_and_configure_window(ITensorInfo *inpu
unsigned int &num_elems_processed_per_iteration_y = num_elements_processed[1];
bool reinterpret_input_as_3d = reshape_info.reinterpret_input_as_3d();
bool reinterpret_output_as_3d = (reshape_info.depth_output_gemm3d() != 0);
- const bool has_vec_c = input2 != nullptr && beta != 0.f;
// In case both input and output have to be reinterpreted as 3D tensors,
// force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.
@@ -194,12 +210,23 @@ inline std::pair<Status, Window> validate_and_configure_window(ITensorInfo *inpu
ceil_to_multiple(output->dimension(0), num_elems_processed_per_iteration_x),
output->dimension(1) + bottom_pad);
- window_changed = update_window_and_padding(win, input0_access, input1_access) || // window used by the execute_window_loop
- update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor
- if(has_vec_c)
+ if(input2 != nullptr)
+ {
+ const int bias_processed_per_iteration_x = num_elems_processed_per_iteration_x;
+
+ const int bias_processed_per_iteration_y = reshape_info.broadcast_bias() ? 1 : num_elems_processed_per_iteration_y;
+
+ AccessWindowStatic input2_access(input2, 0, 0,
+ ceil_to_multiple(input2->dimension(0), bias_processed_per_iteration_x),
+ ceil_to_multiple(input2->dimension(1), bias_processed_per_iteration_y));
+
+ window_changed = update_window_and_padding(win, input0_access, input1_access, input2_access) || // window used by the execute_window_loop
+ update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor
+ }
+ else
{
- AccessWindowHorizontal input2_access(input2, 0, num_elems_processed_per_iteration_x);
- window_changed = window_changed || update_window_and_padding(win, input2_access);
+ window_changed = update_window_and_padding(win, input0_access, input1_access) || // window used by the execute_window_loop
+ update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor
}
output_access.set_valid_region(win_out, ValidRegion(Coordinates(0, 0), output->tensor_shape()));
@@ -232,12 +259,23 @@ inline std::pair<Status, Window> validate_and_configure_window(ITensorInfo *inpu
ceil_to_multiple(output->dimension(0), num_elems_processed_per_iteration_x),
output->dimension(1) + bottom_pad);
- window_changed = update_window_and_padding(win, input0_access, input1_access) || // window used by the execute_window_loop
- update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor
- if(has_vec_c)
+ if(input2 != nullptr)
+ {
+ const int bias_processed_per_iteration_x = num_elems_processed_per_iteration_x;
+
+ const int bias_processed_per_iteration_y = reshape_info.broadcast_bias() ? 1 : num_elems_processed_per_iteration_y;
+
+ AccessWindowStatic input2_access(input2, 0, 0,
+ ceil_to_multiple(input2->dimension(0), bias_processed_per_iteration_x),
+ ceil_to_multiple(input2->dimension(1), bias_processed_per_iteration_y));
+
+ window_changed = update_window_and_padding(win, input0_access, input1_access, input2_access) || // window used by the execute_window_loop
+ update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor
+ }
+ else
{
- AccessWindowHorizontal input2_access(input2, 0, num_elems_processed_per_iteration_x);
- window_changed = window_changed || update_window_and_padding(win, input2_access);
+ window_changed = update_window_and_padding(win, input0_access, input1_access) || // window used by the execute_window_loop
+ update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor
}
Coordinates coord;
@@ -257,12 +295,13 @@ inline std::pair<Status, Window> validate_and_configure_window(ITensorInfo *inpu
} // namespace
CLGEMMMatrixMultiplyKernel::CLGEMMMatrixMultiplyKernel()
- : _input0(nullptr), _input1(nullptr), _input2(nullptr), _output(nullptr), _slide_matrix_b(true), _reinterpret_input_as_3d(false), _reinterpret_output_as_3d(false), _has_vec_c(false)
+ : _input0(nullptr), _input1(nullptr), _input2(nullptr), _output(nullptr), _slide_matrix_b(true), _reinterpret_input_as_3d(false), _reinterpret_output_as_3d(false), _add_bias(false),
+ _broadcast_bias(false)
{
}
void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta,
- bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, bool fp_mixed_precision)
+ bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, bool fp_mixed_precision, const ActivationLayerInfo &activation_info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
@@ -272,10 +311,12 @@ void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTen
_input0 = input0;
_input1 = input1;
- _input2 = input2;
+ _input2 = helpers::float_ops::is_zero(beta) ? nullptr : input2;
_output = output;
_reinterpret_input_as_3d = reshape_info.reinterpret_input_as_3d();
_reinterpret_output_as_3d = (reshape_info.depth_output_gemm3d() != 0);
+ _add_bias = _input2 != nullptr;
+ _broadcast_bias = reshape_info.broadcast_bias();
// In case both input and output have to be reinterpreted as 3D tensors,
// force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.
@@ -306,23 +347,21 @@ void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTen
// Create build options
CLBuildOptions build_opts;
- // Only define ALPHA when alpha is not 1.0f. This avoids performing unnecessary multiplications.
- if(!(helpers::float_ops::is_one(alpha)))
- {
- build_opts.add_option("-DALPHA=" + float_to_string_with_full_precision(alpha));
- }
+ build_opts.add_option_if(!(helpers::float_ops::is_one(alpha)), "-DALPHA=" + float_to_string_with_full_precision(alpha));
+ build_opts.add_option_if(_input2 != nullptr, "-DBETA=" + float_to_string_with_full_precision(beta));
+ build_opts.add_option_if(helpers::float_ops::is_one(beta), "-DUNIT_BETA");
+ build_opts.add_option_if(reshape_info.broadcast_bias(), "-DBROADCAST_BIAS");
build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D");
build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D");
build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(1)));
build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(2)));
-
- // Do not slide matrix B if _slide_matrix_b = false
build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2)));
+ build_opts.add_option_if(activation_info.enabled(), "-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(activation_info.activation())));
+ build_opts.add_option_if(activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(activation_info.a()));
+ build_opts.add_option_if(activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(activation_info.b()));
const bool is_bifrost = get_arch_from_target(gpu_target) == GPUTarget::BIFROST;
- _has_vec_c = input2 != nullptr && beta != 0.f;
-
std::string kernel_name;
if(is_interleaved_transposed)
{
@@ -386,15 +425,14 @@ void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTen
build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_X=" + support::cpp11::to_string(num_elements_processed.x()));
}
- // Configure matrix C addition if necessary
- build_opts.add_option_if(_has_vec_c, "-DADD_VEC_C");
-
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
// Set config_id for enabling LWS tuning
_config_id = "gemm_";
_config_id += (is_interleaved_transposed ? "reshaped_" : "");
+ _config_id += (_add_bias ? "add_bias_" : "");
+ _config_id += (_broadcast_bias ? "broadcast_bias_" : "");
_config_id += (fp_mixed_precision ? "fp_mixed_" : "");
_config_id += (_reinterpret_input_as_3d ? "3di_" : "");
_config_id += (_reinterpret_output_as_3d ? "3do_" : "");
@@ -412,11 +450,12 @@ void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTen
}
Status CLGEMMMatrixMultiplyKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float alpha, float beta,
- bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, GPUTarget gpu_target, bool fp_mixed_precision)
+ bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, GPUTarget gpu_target, bool fp_mixed_precision, const ActivationLayerInfo &activation_info)
{
// Note: num_elements_processed will be set in validate_and_configure_window()
ElementsProcessed num_elements_processed{};
ARM_COMPUTE_UNUSED(alpha);
+ ARM_COMPUTE_UNUSED(activation_info);
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, input2, output, beta, is_interleaved_transposed, reshape_info, fp_mixed_precision));
ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(),
input1->clone().get(),
@@ -449,12 +488,12 @@ void CLGEMMMatrixMultiplyKernel::run(const Window &window, cl::CommandQueue &que
slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1));
slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1));
- const unsigned int num_arguments_vec_c = (_has_vec_c) ? num_arguments_per_1D_tensor() : 0;
+ const unsigned int num_arguments_bias = _add_bias ? num_arguments_per_2D_tensor() + 1 : 0;
if(_reinterpret_input_as_3d)
{
// Pass bottom paddings to the kernel if the input has to be reinterpreted as 3D tensor
- const unsigned int idx0 = 3 * num_arguments_per_2D_tensor() + 3 + num_arguments_vec_c;
+ const unsigned int idx0 = 3 * num_arguments_per_2D_tensor() + 3 + num_arguments_bias;
const unsigned int total_cross_plane_pad = _input0->info()->padding().top + _input0->info()->padding().bottom;
_kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
}
@@ -462,7 +501,7 @@ void CLGEMMMatrixMultiplyKernel::run(const Window &window, cl::CommandQueue &que
if(_reinterpret_output_as_3d)
{
// Pass bottom paddings to the kernel if the output has to be reinterpreted as 3D tensor
- const unsigned int idx0 = 3 * num_arguments_per_2D_tensor() + 3 + (_reinterpret_input_as_3d ? 1 : 0) + num_arguments_vec_c;
+ const unsigned int idx0 = 3 * num_arguments_per_2D_tensor() + 3 + (_reinterpret_input_as_3d ? 1 : 0) + num_arguments_bias;
const unsigned int total_cross_plane_pad = _output->info()->padding().top + _output->info()->padding().bottom;
_kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
}
@@ -480,13 +519,17 @@ void CLGEMMMatrixMultiplyKernel::run(const Window &window, cl::CommandQueue &que
unsigned int idx = 0;
add_2D_tensor_argument(idx, _input0, slice);
add_2D_tensor_argument(idx, _input1, slice_b);
- if(_has_vec_c)
+ if(_add_bias)
{
- add_1D_tensor_argument(idx, _input2, slice);
+ add_2D_tensor_argument(idx, _input2, slice);
}
add_2D_tensor_argument(idx, _output, slice);
_kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[2]));
_kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[2]));
+ if(_add_bias)
+ {
+ _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input2->info()->strides_in_bytes()[2]));
+ }
_kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[2]));
enqueue(queue, *this, slice, lws_hint());
}