diff options
Diffstat (limited to 'src/core/CL/cl_kernels/direct_convolution3x3.cl')
-rw-r--r-- | src/core/CL/cl_kernels/direct_convolution3x3.cl | 227 |
1 files changed, 203 insertions, 24 deletions
diff --git a/src/core/CL/cl_kernels/direct_convolution3x3.cl b/src/core/CL/cl_kernels/direct_convolution3x3.cl index 824306f2ba..08d25f6741 100644 --- a/src/core/CL/cl_kernels/direct_convolution3x3.cl +++ b/src/core/CL/cl_kernels/direct_convolution3x3.cl @@ -66,6 +66,185 @@ acc = ADD_OP(acc, MUL_OP((VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s2468, src0.sACE, src1), (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s2)); \ }) +#if defined(DATA_LAYOUT_NHWC) + +#define PTR_TO_VALUE(PTR, DATA_TYPE) *((__global DATA_TYPE *)(PTR)) + +#if STRIDE_X == 1 +#define CONVOLUTION1x3_NHWC(acc, row_ptr, weights_ptr) CONVOLUTION1x3_STRIDE_NHWC_STRIDE1(acc, row_ptr, weights_ptr) +#elif STRIDE_X == 2 /* STRIDE_X == 1 */ +#define CONVOLUTION1x3_NHWC(acc, row_ptr, weights_ptr) CONVOLUTION1x3_STRIDE_NHWC_STRIDE2(acc, row_ptr, weights_ptr) +#else /* STRIDE_X not equals 1 or 2 */ +#error "STRIDE_X larger than 2 is not supported" +#endif /* STRIDE_X == 2 */ + +#define CONVOLUTION1x3_STRIDE_NHWC_STRIDE1(acc, row_ptr, weights_ptr) \ + { \ + VEC_DATA_TYPE(DATA_TYPE, 8) \ + src0 = (VEC_DATA_TYPE(DATA_TYPE, 8))( \ + PTR_TO_VALUE(row_ptr + 0 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 1 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 2 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 3 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 4 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 5 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 6 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 7 * src_stride_y, DATA_TYPE)); \ + VEC_DATA_TYPE(DATA_TYPE, 2) \ + src1 = (VEC_DATA_TYPE(DATA_TYPE, 2))( \ + PTR_TO_VALUE(row_ptr + 8 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 9 * src_stride_y, DATA_TYPE)); \ + VEC_DATA_TYPE(DATA_TYPE, 3) \ + weights = (VEC_DATA_TYPE(DATA_TYPE, 3))( \ + PTR_TO_VALUE((weights_ptr) + 0 * weights_stride_y, DATA_TYPE), \ + PTR_TO_VALUE((weights_ptr) + 1 * weights_stride_y, DATA_TYPE), \ + PTR_TO_VALUE((weights_ptr) + 2 * weights_stride_y, DATA_TYPE)); \ + acc = ADD_OP(acc, MUL_OP(src0, (VEC_DATA_TYPE(DATA_TYPE, 8))weights.s0)); \ + acc = ADD_OP(acc, MUL_OP((VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s1234, src0.s567, src1.s0), (VEC_DATA_TYPE(DATA_TYPE, 8))weights.s1)); \ + acc = ADD_OP(acc, MUL_OP((VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s234, src0.s567, src1.s01), (VEC_DATA_TYPE(DATA_TYPE, 8))weights.s2)); \ + } + +#define CONVOLUTION1x3_STRIDE_NHWC_STRIDE2(acc, row_ptr, weights_ptr) \ + { \ + VEC_DATA_TYPE(DATA_TYPE, 16) \ + src0 = (VEC_DATA_TYPE(DATA_TYPE, 16))( \ + PTR_TO_VALUE(row_ptr + 0 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 1 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 2 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 3 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 4 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 5 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 6 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 7 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 8 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 9 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 10 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 11 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 12 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 13 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 14 * src_stride_y, DATA_TYPE), \ + PTR_TO_VALUE(row_ptr + 15 * src_stride_y, DATA_TYPE)); \ + DATA_TYPE src1 = PTR_TO_VALUE(row_ptr + 16 * src_stride_y, DATA_TYPE); \ + VEC_DATA_TYPE(DATA_TYPE, 3) \ + weights = (VEC_DATA_TYPE(DATA_TYPE, 3))( \ + PTR_TO_VALUE((weights_ptr) + 0 * weights_stride_y, DATA_TYPE), \ + PTR_TO_VALUE((weights_ptr) + 1 * weights_stride_y, DATA_TYPE), \ + PTR_TO_VALUE((weights_ptr) + 2 * weights_stride_y, DATA_TYPE)); \ + \ + acc = ADD_OP(acc, MUL_OP(src0.s02468ACE, (VEC_DATA_TYPE(DATA_TYPE, 8))weights.s0)); \ + acc = ADD_OP(acc, MUL_OP((VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s1357, src0.s9BDF), (VEC_DATA_TYPE(DATA_TYPE, 8))weights.s1)); \ + acc = ADD_OP(acc, MUL_OP((VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s2468, src0.sACE, src1), (VEC_DATA_TYPE(DATA_TYPE, 8))weights.s2)); \ + } + +/** This kernel performs a direct convolution to convolve the low three dimensions. + * + * @note This OpenCL kernel works with stride_x = 1 and 2 + * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float + * @note The third dimensions of the weights tensors must be passed at compile time using -DWEIGHTS_DEPTH + * @note If biases are used then -DHAS_BIAS has to be passed at compile time + * + * @param[in] src_ptr Pointer to the source tensor. Supported data types: QS8/QS16/F16/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[in] weights_ptr Pointer to the weights tensor. Supported data types: same as @p src_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_convolution3x3_nhwc( + TENSOR3D_DECLARATION(src), + TENSOR3D_DECLARATION(dst), + TENSOR3D_DECLARATION(weights), +#ifdef HAS_BIAS + VECTOR_DECLARATION(biases), +#endif /* defined(HAS_BIAS) */ + unsigned int weights_stride_w) +{ + Image src = CONVERT_TO_IMAGE_STRUCT(src); + Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(weights); + Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); + + VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 8) + values0 = 0; + const int id0 = get_global_id(0); + const int id1 = get_global_id(1); + const int id2 = get_global_id(2); + + __global uchar *weights_addr = (__global uchar *)tensor3D_offset(&weights, 0, 0, 0); + __global uchar *src_addr = (__global uchar *)offset(&src, 0, 0) - src_stride_x * id0 + ((id2 * STRIDE_Y) - PAD_TOP) * (int)src_stride_z; + + weights_addr += id0 * weights_stride_w; + + const int coordy = ((id2 * STRIDE_Y) - PAD_TOP); + for(volatile int d = 0; d < WEIGHTS_DEPTH; ++d) + { +#if PAD_TOP > 0 + if(coordy < 0) // special case Z = -1 doesn't exists + { + //skip first row and load the two next ones + CONVOLUTION1x3_NHWC(values0, src_addr + 1 * (int)src_stride_z, (weights_addr + 1 * (int)weights_stride_z)); + CONVOLUTION1x3_NHWC(values0, src_addr + 2 * (int)src_stride_z, (weights_addr + 2 * (int)weights_stride_z)); + } + else if(coordy == (SRC_HEIGHT - PAD_TOP - 1)) + { + // special case when computing the last row of the output we must read the last three rows from the input buffer (including padding) but the + // Z axis has no padding at all. + CONVOLUTION1x3_NHWC(values0, src_addr, (weights_addr + 0 * (int)weights_stride_z)); + CONVOLUTION1x3_NHWC(values0, src_addr + 1 * (int)src_stride_z, (weights_addr + 1 * (int)weights_stride_z)); + } + else + { + CONVOLUTION1x3_NHWC(values0, src_addr, (weights_addr + 0 * (int)weights_stride_z)); + CONVOLUTION1x3_NHWC(values0, src_addr + 1 * (int)src_stride_z, (weights_addr + 1 * (int)weights_stride_z)); + CONVOLUTION1x3_NHWC(values0, src_addr + 2 * (int)src_stride_z, (weights_addr + 2 * (int)weights_stride_z)); + } +#else // PAD_TOP > 0 + CONVOLUTION1x3_NHWC(values0, src_addr, (weights_addr + 0 * (int)weights_stride_z)); + CONVOLUTION1x3_NHWC(values0, src_addr + 1 * (int)src_stride_z, (weights_addr + 1 * (int)weights_stride_z)); + CONVOLUTION1x3_NHWC(values0, src_addr + 2 * (int)src_stride_z, (weights_addr + 2 * (int)weights_stride_z)); +#endif // PAD_TOP > 0 + src_addr += src_stride_x; + weights_addr += weights_stride_x; + } + +#ifdef HAS_BIAS + Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases); + values0 = ADD_OP(values0, (VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 8)) * ((__global DATA_TYPE *)(vector_offset(&biases, id0)))); +#endif /* defined(HAS_BIAS) */ + + *((__global DATA_TYPE *)(dst.ptr + 0 * dst_stride_y)) = values0.s0; + *((__global DATA_TYPE *)(dst.ptr + 1 * dst_stride_y)) = values0.s1; + *((__global DATA_TYPE *)(dst.ptr + 2 * dst_stride_y)) = values0.s2; + *((__global DATA_TYPE *)(dst.ptr + 3 * dst_stride_y)) = values0.s3; + *((__global DATA_TYPE *)(dst.ptr + 4 * dst_stride_y)) = values0.s4; + *((__global DATA_TYPE *)(dst.ptr + 5 * dst_stride_y)) = values0.s5; + *((__global DATA_TYPE *)(dst.ptr + 6 * dst_stride_y)) = values0.s6; + *((__global DATA_TYPE *)(dst.ptr + 7 * dst_stride_y)) = values0.s7; +} +#endif // defined(DATA_LAYOUT_NHWC) + /** This kernel performs a direct convolution to convolve the low three dimensions. * * @note This OpenCL kernel works with stride_x = 1 and 2 @@ -117,7 +296,7 @@ __kernel void direct_convolution3x3( Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 8) - pixels0 = 0; + values0 = 0; __global uchar *weights_addr = (__global uchar *)tensor3D_offset(&weights, 0, 0, 0); __global uchar *src_addr = (__global uchar *)offset(&src, 0, 0); @@ -127,9 +306,9 @@ __kernel void direct_convolution3x3( for(volatile int d = 0; d < WEIGHTS_DEPTH; ++d) { - CONVOLUTION1x3(pixels0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_y)); - CONVOLUTION1x3(pixels0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_y)); - CONVOLUTION1x3(pixels0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_y)); + CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_y)); + CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_y)); + CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_y)); src_addr += src_stride_z; weights_addr += weights_stride_z; @@ -138,10 +317,10 @@ __kernel void direct_convolution3x3( #ifdef HAS_BIAS Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases); - pixels0 = ADD_OP(pixels0, (VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 8)) * ((__global DATA_TYPE *)(vector_offset(&biases, kernel_index)))); + values0 = ADD_OP(values0, (VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 8)) * ((__global DATA_TYPE *)(vector_offset(&biases, kernel_index)))); #endif /* defined(HAS_BIAS) */ - vstore8(CONVERT_SAT(pixels0, VEC_DATA_TYPE(DATA_TYPE, 8)), 0, (__global DATA_TYPE *)dst.ptr); + vstore8(CONVERT_SAT(values0, VEC_DATA_TYPE(DATA_TYPE, 8)), 0, (__global DATA_TYPE *)dst.ptr); } #endif //defined(DATA_TYPE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH) @@ -214,9 +393,9 @@ __kernel void direct_convolution3x3_f32_bifrost( Image src = CONVERT_TO_IMAGE_STRUCT(src); Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); - float4 pixels0 = 0; - float4 pixels1 = 0; - float4 pixels2 = 0; + float4 values0 = 0; + float4 values1 = 0; + float4 values2 = 0; __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); @@ -236,39 +415,39 @@ __kernel void direct_convolution3x3_f32_bifrost( src0 = vload4(0, (__global float *)(src_addr + 0 * src_stride_y)); src1 = vload2(0, (__global float *)(src_addr + 0 * src_stride_y) + 4); - CONVOLUTION1x3_BIFROST(pixels0, src0, src1, weights_row0); + CONVOLUTION1x3_BIFROST(values0, src0, src1, weights_row0); // Load values from row1 of input tensor src0 = vload4(0, (__global float *)(src_addr + 1 * src_stride_y)); src1 = vload2(0, (__global float *)(src_addr + 1 * src_stride_y) + 4); // Accumulate - CONVOLUTION1x3_BIFROST(pixels0, src0, src1, weights_row1); - CONVOLUTION1x3_BIFROST(pixels1, src0, src1, weights_row0); + CONVOLUTION1x3_BIFROST(values0, src0, src1, weights_row1); + CONVOLUTION1x3_BIFROST(values1, src0, src1, weights_row0); // Load values from row2 of input tensor src0 = vload4(0, (__global float *)(src_addr + 2 * src_stride_y)); src1 = vload2(0, (__global float *)(src_addr + 2 * src_stride_y) + 4); // Accumulate - CONVOLUTION1x3_BIFROST(pixels0, src0, src1, weights_row2); - CONVOLUTION1x3_BIFROST(pixels1, src0, src1, weights_row1); - CONVOLUTION1x3_BIFROST(pixels2, src0, src1, weights_row0); + CONVOLUTION1x3_BIFROST(values0, src0, src1, weights_row2); + CONVOLUTION1x3_BIFROST(values1, src0, src1, weights_row1); + CONVOLUTION1x3_BIFROST(values2, src0, src1, weights_row0); // Load values from row3 of input tensor src0 = vload4(0, (__global float *)(src_addr + 3 * src_stride_y)); src1 = vload2(0, (__global float *)(src_addr + 3 * src_stride_y) + 4); // Accumulate - CONVOLUTION1x3_BIFROST(pixels1, src0, src1, weights_row2); - CONVOLUTION1x3_BIFROST(pixels2, src0, src1, weights_row1); + CONVOLUTION1x3_BIFROST(values1, src0, src1, weights_row2); + CONVOLUTION1x3_BIFROST(values2, src0, src1, weights_row1); // Row4 src0 = vload4(0, (__global float *)(src_addr + 4 * src_stride_y)); src1 = vload2(0, (__global float *)(src_addr + 4 * src_stride_y) + 4); // Accumulate - CONVOLUTION1x3_BIFROST(pixels2, src0, src1, weights_row2); + CONVOLUTION1x3_BIFROST(values2, src0, src1, weights_row2); src_addr += src_stride_z; weights_addr += weights_stride_z; @@ -279,13 +458,13 @@ __kernel void direct_convolution3x3_f32_bifrost( float bias = (float) * ((__global float *)(vector_offset(&biases, kernel_index))); - pixels0 += (float4)bias; - pixels1 += (float4)bias; - pixels2 += (float4)bias; + values0 += (float4)bias; + values1 += (float4)bias; + values2 += (float4)bias; #endif /* defined(HAS_BIAS) */ - vstore4(pixels0, 0, (__global float *)(dst.ptr + 0 * dst_stride_y)); - vstore4(pixels1, 0, (__global float *)(dst.ptr + 1 * dst_stride_y)); - vstore4(pixels2, 0, (__global float *)(dst.ptr + 2 * dst_stride_y)); + vstore4(values0, 0, (__global float *)(dst.ptr + 0 * dst_stride_y)); + vstore4(values1, 0, (__global float *)(dst.ptr + 1 * dst_stride_y)); + vstore4(values2, 0, (__global float *)(dst.ptr + 2 * dst_stride_y)); } #endif // defined(WEIGHTS_DEPTH) |