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authorGian Marco Iodice <gianmarco.iodice@arm.com>2017-09-06 17:24:25 +0100
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:35:24 +0000
commit1c8409d7ce90ea449437076574c98a4ea90d9368 (patch)
tree8bd786b274ba9d905af803b481eccfa7635053f9 /src/core
parent898a806bd0c72aeafb3557efdbc686aab54992d9 (diff)
downloadComputeLibrary-1c8409d7ce90ea449437076574c98a4ea90d9368.tar.gz
COMPMID-477 - Optimized CLDirectConvolution1x1 for Bifrost
- Fixed bug in CLDirectConvolution3x3 Change-Id: Iaf34ef44f0b7bc02e66f3eb4452ff7a90ef83523 Reviewed-on: http://mpd-gerrit.cambridge.arm.com/86725 Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com> Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com> Reviewed-by: Moritz Pflanzer <moritz.pflanzer@arm.com>
Diffstat (limited to 'src/core')
-rw-r--r--src/core/CL/CLKernelLibrary.cpp1
-rw-r--r--src/core/CL/cl_kernels/direct_convolution1x1.cl122
-rw-r--r--src/core/CL/cl_kernels/direct_convolution3x3.cl8
-rw-r--r--src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp10
4 files changed, 135 insertions, 6 deletions
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index 03c9903d6d..dd549f035b 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -148,6 +148,7 @@ const std::map<std::string, std::string> CLKernelLibrary::_kernel_program_map =
{ "derivative", "derivative.cl" },
{ "dilate", "dilate.cl" },
{ "direct_convolution1x1", "direct_convolution1x1.cl" },
+ { "direct_convolution1x1_f32_bifrost", "direct_convolution1x1.cl" },
{ "direct_convolution3x3", "direct_convolution3x3.cl" },
{ "direct_convolution3x3_f32_bifrost", "direct_convolution3x3.cl" },
{ "direct_convolution5x5", "direct_convolution5x5.cl" },
diff --git a/src/core/CL/cl_kernels/direct_convolution1x1.cl b/src/core/CL/cl_kernels/direct_convolution1x1.cl
index 2aa999a80f..fb516ddd6e 100644
--- a/src/core/CL/cl_kernels/direct_convolution1x1.cl
+++ b/src/core/CL/cl_kernels/direct_convolution1x1.cl
@@ -41,6 +41,8 @@ MULQ_SAT_IMPL(qs32x8, qs32x8)
#endif /* FIXED_POINT_POSITION */
+#if defined(DATA_TYPE) && defined(DATA_SIZE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH)
+
#if STRIDE_X == 3
#define INPUT_PIXEL_STR(data_size) extract_input_stride3_##data_size
#define INPUT_PIXEL(data_size) INPUT_PIXEL_STR(data_size)
@@ -165,7 +167,6 @@ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3_8(__global const DATA_T
* @param[in] biases_offset_first_element_in_bytes The offset of the first element in the biases tensor
* @param[in] weights_stride_w Stride of the weights tensor in the 4th dimension
*/
-#if defined(DATA_TYPE) && defined(DATA_SIZE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH)
__kernel void direct_convolution1x1(
TENSOR3D_DECLARATION(src),
TENSOR3D_DECLARATION(dst),
@@ -207,3 +208,122 @@ __kernel void direct_convolution1x1(
vstore8(CONVERT_SAT(pixels, VEC_DATA_TYPE(DATA_TYPE, 8)), 0, (__global DATA_TYPE *)dst.ptr);
}
#endif // defined(DATA_TYPE) && defined(DATA_SIZE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH)
+
+#if defined(WEIGHTS_DEPTH)
+
+#define CONVOLUTION1x1_BIFROST(acc, src, weight_value) \
+ ({ \
+ acc.s0 = mad(src.s0, weight_value, acc.s0); \
+ acc.s1 = mad(src.s1, weight_value, acc.s1); \
+ acc.s2 = mad(src.s2, weight_value, acc.s2); \
+ acc.s3 = mad(src.s3, weight_value, acc.s3); \
+ })
+
+/** An optimized direct convolution 1x1 OpenCL kernel for Bifrost architectures when the data type is F32
+ *
+ * @note This OpenCL kernel works only with stride_x and stride_y equal to 1
+ * @note The third dimensions of the weights tensors must be passed at compile time using -DWEIGHTS_DEPTH
+ * @note In case biases, -DHAS_BIAS must to be passed at compile
+ *
+ * @param[in] src_ptr Pointer to the source tensor. Supported data types: F32
+ * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes)
+ * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
+ * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
+ * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
+ * @param[in] dst_stride_x Stride of the destination tensor 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 tensor in Y dimension (in bytes)
+ * @param[in] dst_step_y dst_stride_y * number of elements along Z processed per workitem(in bytes)
+ * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
+ * @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
+ * @param[out] weights_ptr Pointer to the weights tensor. Supported data types: same as @p weights_ptr
+ * @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes)
+ * @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes)
+ * @param[in] weights_step_y weights_stride_y * number of elements along y processed per workitem(in bytes)
+ * @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes)
+ * @param[in] weights_step_z weights_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] weights_offset_first_element_in_bytes The offset of the first element in the weights tensor
+ * @param[in] biases_ptr Pointer to the biases tensor. Same as @p src_ptr
+ * @param[in] biases_stride_x Stride of the biases tensor in X dimension (in bytes)
+ * @param[in] biases_step_x biases_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] biases_offset_first_element_in_bytes The offset of the first element in the biases tensor
+ * @param[in] weights_stride_w Stride of the weights tensor in the 4th dimension
+ */
+__kernel void direct_convolution1x1_f32_bifrost(
+ TENSOR3D_DECLARATION(src),
+ TENSOR3D_DECLARATION(dst),
+ TENSOR3D_DECLARATION(weights),
+#ifdef HAS_BIAS
+ VECTOR_DECLARATION(biases),
+#endif /* defined(HAS_BIAS) */
+ unsigned int weights_stride_w)
+{
+ // Get the kernel index
+ const int kernel_index = get_global_id(2);
+
+ Image src = CONVERT_TO_IMAGE_STRUCT(src);
+ Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst);
+
+ float4 acc0 = 0.0f;
+ float4 acc1 = 0.0f;
+ float4 acc2 = 0.0f;
+ float4 acc3 = 0.0f;
+
+ __global uchar *weights_addr = (__global uchar *)(weights_ptr + weights_offset_first_element_in_bytes + kernel_index * weights_stride_w);
+ __global uchar *src_addr = (__global uchar *)offset(&src, 0, 0);
+
+ for(ushort d = 0; d < (ushort)WEIGHTS_DEPTH; ++d)
+ {
+ // Load the weights
+ float weight = *((__global float *)weights_addr);
+
+ // Load values from row0 of input tensor
+ float4 src0 = vload4(0, (__global float *)(src_addr + 0 * src_stride_y));
+ float4 src1 = vload4(0, (__global float *)(src_addr + 1 * src_stride_y));
+ float4 src2 = vload4(0, (__global float *)(src_addr + 2 * src_stride_y));
+ float4 src3 = vload4(0, (__global float *)(src_addr + 3 * src_stride_y));
+
+ CONVOLUTION1x1_BIFROST(acc0, src0, weight);
+ CONVOLUTION1x1_BIFROST(acc1, src1, weight);
+ CONVOLUTION1x1_BIFROST(acc2, src2, weight);
+ CONVOLUTION1x1_BIFROST(acc3, src3, weight);
+
+ src_addr += src_stride_z;
+ weights_addr += weights_stride_z;
+ }
+
+#ifdef HAS_BIAS
+ Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases);
+
+ float bias = (float) * ((__global float *)(vector_offset(&biases, kernel_index)));
+
+ acc0.s0 += bias;
+ acc0.s1 += bias;
+ acc0.s2 += bias;
+ acc0.s3 += bias;
+ acc1.s0 += bias;
+ acc1.s1 += bias;
+ acc1.s2 += bias;
+ acc1.s3 += bias;
+ acc2.s0 += bias;
+ acc2.s1 += bias;
+ acc2.s2 += bias;
+ acc2.s3 += bias;
+ acc3.s0 += bias;
+ acc3.s1 += bias;
+ acc3.s2 += bias;
+ acc3.s3 += bias;
+#endif /* defined(HAS_BIAS) */
+
+ vstore4(acc0, 0, (__global float *)(dst.ptr + 0 * dst_stride_y));
+ vstore4(acc1, 0, (__global float *)(dst.ptr + 1 * dst_stride_y));
+ vstore4(acc2, 0, (__global float *)(dst.ptr + 2 * dst_stride_y));
+ vstore4(acc3, 0, (__global float *)(dst.ptr + 3 * dst_stride_y));
+}
+#endif // defined(WEIGHTS_DEPTH) \ No newline at end of file
diff --git a/src/core/CL/cl_kernels/direct_convolution3x3.cl b/src/core/CL/cl_kernels/direct_convolution3x3.cl
index 26f24e187b..1a228dd74c 100644
--- a/src/core/CL/cl_kernels/direct_convolution3x3.cl
+++ b/src/core/CL/cl_kernels/direct_convolution3x3.cl
@@ -288,11 +288,11 @@ __kernel void direct_convolution3x3_f32_bifrost(
#ifdef HAS_BIAS
Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases);
- float4 bias = (float4) * ((__global float *)(vector_offset(&biases, kernel_index)));
+ float bias = (float) * ((__global float *)(vector_offset(&biases, kernel_index)));
- pixels0 += bias;
- pixels1 += bias;
- pixels2 += bias;
+ pixels0 += (float4)bias;
+ pixels1 += (float4)bias;
+ pixels2 += (float4)bias;
#endif /* defined(HAS_BIAS) */
vstore4(pixels0, 0, (__global float *)(dst.ptr + 0 * dst_stride_y));
diff --git a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
index 265c5074c5..75e6d5e971 100644
--- a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
+++ b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
@@ -108,7 +108,7 @@ void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICL
options.emplace("-DHAS_BIAS");
}
- if((gpu_target == GPUTarget::BIFROST) && (kernel_size <= 5) && (kernel_size != 1) && (_conv_stride_x == 1) && (_conv_stride_y == 1) && (input->info()->data_type() == DataType::F32))
+ if((gpu_target == GPUTarget::BIFROST) && (kernel_size <= 5) && (_conv_stride_x == 1) && (_conv_stride_y == 1) && (input->info()->data_type() == DataType::F32))
{
options.emplace("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(_weights->info()->dimension(2)));
@@ -125,6 +125,14 @@ void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICL
switch(kernel_size)
{
+ case 1:
+ {
+ num_elems_read_per_iteration_x = 4;
+ num_elems_read_per_iteration_y = 4;
+ num_elems_written_per_iteration_x = 4;
+ num_elems_written_per_iteration_y = 4;
+ break;
+ }
case 3:
{
num_elems_read_per_iteration_x = 6;