COMPMID-355 Implement CL DirectConvolution1x1

* Add FP16 to validation tests.
* Complete benchmark tests for CL and NEON Direct Convolution.

Change-Id: Ie73d8580832372db01b82b39786fd9c8be560090
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/82014
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>

1 files changed, 190 insertions, 0 deletions

diff --git a/src/core/CL/cl_kernels/direct_convolution1x1.cl b/src/core/CL/cl_kernels/direct_convolution1x1.cl
new file mode 100644
index 0000000000..d161f80fea
--- /dev/null
+++ b/src/core/CL/cl_kernels/direct_convolution1x1.cl
@@ -0,0 +1,190 @@
+/*
+ * Copyright (c) 2016, 2017 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "helpers.h"
+
+#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)
+#elif STRIDE_X == 2
+#define INPUT_PIXEL(data_size) extract_input_stride2
+#elif STRIDE_X == 1
+#define INPUT_PIXEL(data_size) extract_input_stride1
+#else /* STRIDE_X not equals 1, 2 or 3 */
+#error "Only support strides 1, 2 and 3"
+#endif /* STRIDE_X == 3 */
+
+/** Extracts a 1D horizontal vector from the input tensor with stride as 1.
+ *
+ * @param[in] input_pixel Pointer to the first pixel.
+ *
+ * @return extracted input pixels.
+ */
+inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride1(__global const DATA_TYPE *input_pixel)
+{
+    return vload8(0, input_pixel);
+}
+
+/** Extracts a 1D horizontal vector from the input tensor with stride as 2.
+ *
+ * @param[in] input_pixel Pointer to the first pixel.
+ *
+ * @return extracted input pixels.
+ */
+inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride2(__global const DATA_TYPE *input_pixel)
+{
+    VEC_DATA_TYPE(DATA_TYPE, 16)
+    temp = vload16(0, input_pixel);
+    return temp.s02468ace;
+}
+
+/** Extracts a 1D horizontal vector from the input tensor with stride as 3 and 32-bit data size.
+ *
+ * @param[in] input_pixel Pointer to the first pixel.
+ *
+ * @return extracted input pixels.
+ */
+inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3_32(__global const DATA_TYPE *input_pixel)
+{
+    VEC_DATA_TYPE(DATA_TYPE, 4)
+    temp1 = vload4(0, input_pixel);
+    VEC_DATA_TYPE(DATA_TYPE, 4)
+    temp2 = vload4(0, input_pixel + 6);
+    VEC_DATA_TYPE(DATA_TYPE, 4)
+    temp3 = vload4(0, input_pixel + 12);
+    VEC_DATA_TYPE(DATA_TYPE, 4)
+    temp4 = vload4(0, input_pixel + 18);
+    return (VEC_DATA_TYPE(DATA_TYPE, 8))(temp1.s03, temp2.s03, temp3.s03, temp4.s03);
+}
+
+/** Extracts a 1D horizontal vector from the input tensor with stride as 3 and 16-bit data size.
+ *
+ * @param[in] input_pixel Pointer to the first pixel.
+ *
+ * @return extracted input pixels.
+ */
+inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3_16(__global const DATA_TYPE *input_pixel)
+{
+    VEC_DATA_TYPE(DATA_TYPE, 8)
+    temp1 = vload8(0, input_pixel);
+    VEC_DATA_TYPE(DATA_TYPE, 8)
+    temp2 = vload8(0, input_pixel + 8);
+    VEC_DATA_TYPE(DATA_TYPE, 8)
+    temp3 = vload8(0, input_pixel + 16);
+    return (VEC_DATA_TYPE(DATA_TYPE, 8))(temp1.s036, temp2.s147, temp3.s25);
+}
+
+/** Extracts a 1D horizontal vector from the input tensor with stride as 3 and 8-bit data size.
+ *
+ * @param[in] input_pixel Pointer to the first pixel.
+ *
+ * @return extracted input pixels.
+ */
+inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3_8(__global const DATA_TYPE *input_pixel)
+{
+    VEC_DATA_TYPE(DATA_TYPE, 16)
+    temp1 = vload16(0, input_pixel);
+    VEC_DATA_TYPE(DATA_TYPE, 16)
+    temp2 = vload16(0, input_pixel + 12);
+    return (VEC_DATA_TYPE(DATA_TYPE, 8))(temp1.s0369, temp2.s0369);
+}
+
+/** This kernel performs a direct convolution to convolve the low three dimensions.
+ *
+ * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float
+ * @note The data size must be passed at compile time using -DDATA_SIZE e.g. -DDATA_SIZE=32
+ * @note The convolution stride x and stride y must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1, _DSTRIDE_Y=1
+ * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row.
+ *
+ * @param[in]  src_ptr                               Pointer to the source tensor. Supported data types: QS8/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[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 W dimension
+ * @param[in]  filter_depth                          The depth size of the filter
+ */
+__kernel void direct_convolution1x1(
+    TENSOR3D_DECLARATION(src),
+    TENSOR3D_DECLARATION(dst),
+    TENSOR3D_DECLARATION(weights),
+#ifdef HAS_BIAS
+    VECTOR_DECLARATION(biases),
+#endif /* defined(HAS_BIAS) */
+    unsigned int weights_stride_w,
+    unsigned int filter_depth)
+{
+    Image    src     = CONVERT_TO_IMAGE_STRUCT(src);
+    Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(weights);
+    Tensor3D dst     = CONVERT_TO_TENSOR3D_STRUCT(dst);
+
+#ifdef HAS_BIAS
+    Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases);
+#endif /* defined(HAS_BIAS) */
+
+    VEC_DATA_TYPE(DATA_TYPE, 8)
+    pixels = 0;
+
+    const uint z_index = get_global_id(2);
+
+    weights.ptr += z_index * weights_stride_w;
+
+    for(int d = 0; d < filter_depth; ++d)
+    {
+        DATA_TYPE weight = *(__global DATA_TYPE *)weights.ptr;
+        VEC_DATA_TYPE(DATA_TYPE, 8)
+        input_pixel = INPUT_PIXEL(DATA_SIZE)((__global DATA_TYPE *)src.ptr);
+        pixels += weight * input_pixel;
+        src.ptr += src_stride_z;
+        weights.ptr += weights_stride_z;
+    }
+
+#ifdef HAS_BIAS
+    pixels += (VEC_DATA_TYPE(DATA_TYPE, 8)) * ((__global DATA_TYPE *)(vector_offset(&biases, z_index)));
+#endif /* defined(HAS_BIAS) */
+
+    vstore8(pixels, 0, (__global DATA_TYPE *)dst.ptr);
+}