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author | Ramy Elgammal <ramy.elgammal@arm.com> | 2023-03-20 10:19:10 +0000 |
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committer | Ramy Elgammal <ramy.elgammal@arm.com> | 2023-03-24 17:12:57 +0000 |
commit | b531b7549abdd5c10b14b00107ea647591baa430 (patch) | |
tree | cf4dad7560fc15df11974de5defc1be1ea106dda /src/core/CL/cl_kernels/common/mat_mul.cl | |
parent | f9a547c448297cc310cad32e2cce2ce1949b4481 (diff) | |
download | ComputeLibrary-b531b7549abdd5c10b14b00107ea647591baa430.tar.gz |
Add Texture Pipe Support for Matmul Lhs T/NT Rhs T kernels
Resolves: COMPMID-5952, COMPMID-5956
Change-Id: Idbd14538e7660792254072fa9631a6f03966f89b
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9371
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/CL/cl_kernels/common/mat_mul.cl')
-rw-r--r-- | src/core/CL/cl_kernels/common/mat_mul.cl | 29 |
1 files changed, 14 insertions, 15 deletions
diff --git a/src/core/CL/cl_kernels/common/mat_mul.cl b/src/core/CL/cl_kernels/common/mat_mul.cl index 90ebf80a6a..90d485e815 100644 --- a/src/core/CL/cl_kernels/common/mat_mul.cl +++ b/src/core/CL/cl_kernels/common/mat_mul.cl @@ -160,11 +160,12 @@ __kernel void mat_mul_native_nt_nt( * @note The block's dimensions used for the LHS and RHS matrices (M0, N0 and K0) must be passed at compile time using -DN0, -DM0 and -DK0 (e.g. -DN0=8, -DM0=4, -DK0=4). * @note The number of leftover outputs rows/columns must be passed using -DPARTIAL_STORE_N0 and -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_N0=2, -DPARTIAL_STORE_M0=3) * @note The dimension K must be passed at compile time using -DK (e.g. -DK=6) + * @note The tensor type ("BUFFER" or "IMAGE") of the rhs tensor must be passed at compile time using -DRHS_TENSOR_TYPE (e.g. -DRHS_TENSOR_TYPE=BUFFER) * @note The kernel name in uppercase must be passed at compile time (e.g. -DMAT_MUL_NATIVE_NT_T) * @note Only the following configurations of M0, N0 and K0 are currently supported: * - M0 > 0 * - N0 = 1, 2, 3, 4, 8, 16 - * - K0 = 1, 2, 3, 4, 8, 16 + * - K0 = 1, 2, 3, 4, 8, 16 (only 4, 8, 16 if RHS_TENSOR_TYPE=IMAGE) * @note Values > 8 for M0, N0 and K0 are not expected to be efficient * * @param[in] lhs_ptr Pointer to the lhs matrix. Supported data types: F32/F16 @@ -174,6 +175,7 @@ __kernel void mat_mul_native_nt_nt( * @param[in] lhs_h The height of the lhs tensor * @param[in] lhs_n Number of the matrices (buffers) in the batch * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the lhs matrix + * @param[in] rhs_img (Optional) Read only cl_image object for the rhs tensor. Included when RHS_TENSOR_TYPE=IMAGE * @param[in] rhs_ptr Pointer to the rhs matrix. Supported data types: same as @p lhs_ptr * @param[in] rhs_stride_y Stride of the rhs matrix in Y (2nd) dimension (in bytes) * @param[in] rhs_stride_z Stride of the rhs tensor in Z (3rd) dimension (in bytes) @@ -190,7 +192,7 @@ __kernel void mat_mul_native_nt_nt( * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the dst matrix */ __kernel void mat_mul_native_nt_t(TENSOR3D_T(lhs, BUFFER), - TENSOR3D_T(rhs, BUFFER), + TENSOR3D_T(rhs, RHS_TENSOR_TYPE), TENSOR3D_T(dst, BUFFER)) { @@ -200,7 +202,6 @@ __kernel void mat_mul_native_nt_t(TENSOR3D_T(lhs, BUFFER), // Compute LHS/RHS/DST matrix address lhs_offset_first_element_in_bytes += y * lhs_stride_y + z * lhs_stride_z; - rhs_offset_first_element_in_bytes += x * rhs_stride_y + z * rhs_stride_z; dst_offset_first_element_in_bytes += x * sizeof(DATA_TYPE) + y * dst_stride_y + z * dst_stride_z; // Initialize the accumulators @@ -211,6 +212,7 @@ __kernel void mat_mul_native_nt_t(TENSOR3D_T(lhs, BUFFER), acc[i].v = 0.f; }) + const int rhs_z = z * rhs_h; int k; for(k = 0; k <= K - K0; k += K0) { @@ -229,7 +231,7 @@ __kernel void mat_mul_native_nt_t(TENSOR3D_T(lhs, BUFFER), // Load tile from the lhs/rhs tensors T_LOAD(DATA_TYPE, M0, K0, BUFFER, lhs, 0, 0, 1, lhs_stride_y, a); - T_LOAD(DATA_TYPE, N0, K0, BUFFER, rhs, 0, 0, 1, rhs_stride_y, b); + T_LOAD(DATA_TYPE, N0, K0, RHS_TENSOR_TYPE, rhs, k, x + rhs_z, 1, rhs_stride_y, b); #if GPU_ARCH == GPU_ARCH_MIDGARD // This part is written to decrease the number of loop unrollings caused @@ -251,7 +253,6 @@ __kernel void mat_mul_native_nt_t(TENSOR3D_T(lhs, BUFFER), #endif // GPU_ARCH == GPU_ARCH_MIDGARD lhs_offset_first_element_in_bytes += K0 * sizeof(DATA_TYPE); - rhs_offset_first_element_in_bytes += K0 * sizeof(DATA_TYPE); } #if K % K0 != 0 @@ -273,7 +274,7 @@ __kernel void mat_mul_native_nt_t(TENSOR3D_T(lhs, BUFFER), // Load tile from the lhs/rhs tensors T_LOAD(DATA_TYPE, M0, 1, BUFFER, lhs, 0, 0, 1, lhs_stride_y, a); - T_LOAD(DATA_TYPE, N0, 1, BUFFER, rhs, 0, 0, 1, rhs_stride_y, b); + T_LOAD(DATA_TYPE, N0, 1, BUFFER, rhs, k, x + rhs_z, 1, rhs_stride_y, b); #if GPU_ARCH == GPU_ARCH_MIDGARD // See the main loop for the explanation of this part @@ -288,7 +289,6 @@ __kernel void mat_mul_native_nt_t(TENSOR3D_T(lhs, BUFFER), #endif // GPU_ARCH == GPU_ARCH_MIDGARD lhs_offset_first_element_in_bytes += 1 * sizeof(DATA_TYPE); - rhs_offset_first_element_in_bytes += 1 * sizeof(DATA_TYPE); } #endif // K % K0 != 0 @@ -464,11 +464,12 @@ __kernel void mat_mul_native_t_nt( * @note The block's dimensions used for the LHS and RHS matrices (M0, N0 and K0) must be passed at compile time using -DN0, -DM0 and -DK0 (e.g. -DN0=8, -DM0=4, -DK0=4). * @note The number of leftover outputs rows/columns must be passed using -DPARTIAL_STORE_N0 and -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_N0=2, -DPARTIAL_STORE_M0=3) * @note The dimension K must be passed at compile time using -DK (e.g. -DK=6) + * @note The tensor type ("BUFFER" or "IMAGE") of the rhs tensor must be passed at compile time using -DRHS_TENSOR_TYPE (e.g. -DRHS_TENSOR_TYPE=BUFFER) * @note The kernel name in uppercase must be passed at compile time (e.g. -DMAT_MUL_NATIVE_T_NT) * @note Only the following configurations of M0, N0 and K0 are currently supported: * - M0 = 1, 2, 3, 4, 8, 16 * - N0 = 1, 2, 3, 4, 8, 16 - * - K0 = 1, 2, 3, 4, 8, 16 + * - K0 = 1, 2, 3, 4, 8, 16 (only 4, 8, 16 if RHS_TENSOR_TYPE=IMAGE) * @note Values > 8 for M0, N0 and K0 are not expected to be efficient * * @param[in] lhs_ptr Pointer to the lhs matrix. Supported data types: F32/F16 @@ -478,6 +479,7 @@ __kernel void mat_mul_native_t_nt( * @param[in] lhs_h The height of the lhs tensor * @param[in] lhs_n Number of the matrices (buffers) in the batch * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the lhs matrix + * @param[in] rhs_img (Optional) Read only cl_image object for the rhs tensor. Included when RHS_TENSOR_TYPE=IMAGE * @param[in] rhs_ptr Pointer to the rhs matrix. Supported data types: same as @p lhs_ptr * @param[in] rhs_stride_y Stride of the rhs matrix in Y (2nd) dimension (in bytes) * @param[in] rhs_stride_z Stride of the rhs tensor in Z (3rd) dimension (in bytes) @@ -495,7 +497,7 @@ __kernel void mat_mul_native_t_nt( */ __kernel void mat_mul_native_t_t( TENSOR3D_T(lhs, BUFFER), - TENSOR3D_T(rhs, BUFFER), + TENSOR3D_T(rhs, RHS_TENSOR_TYPE), TENSOR3D_T(dst, BUFFER)) { const uint x = GET_SPATIAL_IDX(0, N0, PARTIAL_STORE_N0); @@ -504,7 +506,6 @@ __kernel void mat_mul_native_t_t( // Compute LHS/RHS/DST matrix address lhs_offset_first_element_in_bytes += y * sizeof(DATA_TYPE) + z * lhs_stride_z; - rhs_offset_first_element_in_bytes += x * rhs_stride_y + z * rhs_stride_z; dst_offset_first_element_in_bytes += x * sizeof(DATA_TYPE) + y * dst_stride_y + z * dst_stride_z; // Initialize the accumulators @@ -515,6 +516,7 @@ __kernel void mat_mul_native_t_t( acc[i].v = 0.f; }) + const int rhs_z = z * rhs_h; int k; for(k = 0; k <= K - K0; k += K0) { @@ -533,8 +535,7 @@ __kernel void mat_mul_native_t_t( // Load tile from the lhs/rhs tensors T_LOAD(DATA_TYPE, K0, M0, BUFFER, lhs, 0, 0, 1, lhs_stride_y, a); - T_LOAD(DATA_TYPE, N0, K0, BUFFER, rhs, 0, 0, 1, rhs_stride_y, b); - + T_LOAD(DATA_TYPE, N0, K0, RHS_TENSOR_TYPE, rhs, k, x + rhs_z, 1, rhs_stride_y, b); #if GPU_ARCH == GPU_ARCH_MIDGARD // For explanation, see mat_mul_native_nt_t TILE(DATA_TYPE, M0, K0, at); @@ -562,7 +563,6 @@ __kernel void mat_mul_native_t_t( #endif // GPU_ARCH == GPU_ARCH_MIDGARD lhs_offset_first_element_in_bytes += K0 * lhs_stride_y; - rhs_offset_first_element_in_bytes += K0 * sizeof(DATA_TYPE); } #ifdef K % K0 != 0 @@ -584,7 +584,7 @@ __kernel void mat_mul_native_t_t( // Load tile from the lhs/rhs tensors T_LOAD(DATA_TYPE, 1, M0, BUFFER, lhs, 0, 0, 1, lhs_stride_y, a); - T_LOAD(DATA_TYPE, N0, 1, BUFFER, rhs, 0, 0, 1, rhs_stride_y, b); + T_LOAD(DATA_TYPE, N0, 1, BUFFER, rhs, k, x + rhs_z, 1, rhs_stride_y, b); #if GPU_ARCH == GPU_ARCH_MIDGARD // For explanation, see mat_mul_native_nt_t @@ -607,7 +607,6 @@ __kernel void mat_mul_native_t_t( #endif // GPU_ARCH == GPU_ARCH_MIDGARD lhs_offset_first_element_in_bytes += 1 * lhs_stride_y; - rhs_offset_first_element_in_bytes += 1 * sizeof(DATA_TYPE); } #endif // K % K0 != 0 |