aboutsummaryrefslogtreecommitdiff
path: root/src/core/CL/cl_kernels/winograd.cl
diff options
context:
space:
mode:
Diffstat (limited to 'src/core/CL/cl_kernels/winograd.cl')
-rw-r--r--src/core/CL/cl_kernels/winograd.cl247
1 files changed, 175 insertions, 72 deletions
diff --git a/src/core/CL/cl_kernels/winograd.cl b/src/core/CL/cl_kernels/winograd.cl
index 238e21a18a..25c129d0aa 100644
--- a/src/core/CL/cl_kernels/winograd.cl
+++ b/src/core/CL/cl_kernels/winograd.cl
@@ -23,8 +23,102 @@
*/
#include "helpers.h"
-#if defined(NUM_TILES_X)
+#if defined(NUM_CHANNELS)
+
+/** This OpenCL kernel performs Winograd filter transform 3x3 when the data format is NCHW and the output tile is 2x2
+ *
+ * @note The number of channels must be passed at compile time using -DNUM_CHANNELS: e.g. -DNUM_CHANNELS=64
+ *
+ * @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_stride_w Stride of the source tensor in W dimension (in bytes)
+ * @param[in] src_step_w src_stride_w * number of elements along W 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 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] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
+ */
+__kernel void winograd_filter_transform_2x2_3x3_nchw(
+ TENSOR4D_DECLARATION(src),
+ TENSOR3D_DECLARATION(dst))
+{
+ Tensor4D src = CONVERT_TO_TENSOR4D_STRUCT(src, NUM_CHANNELS);
+
+ const __global uchar *src_addr = tensor4D_offset(&src, 0, 0, 0, 0);
+
+ // Load the values from the input tensor
+ float3 w0 = vload3(0, (__global float *)(src_addr + 0 * src_stride_y));
+ float3 w1 = vload3(0, (__global float *)(src_addr + 1 * src_stride_y));
+ float3 w2 = vload3(0, (__global float *)(src_addr + 2 * src_stride_y));
+
+ // Transform the 3x3 tile in a 4x4 tile
+ float4 out0 = 0.0f;
+ float4 out1 = 0.0f;
+ float4 out2 = 0.0f;
+ float4 out3 = 0.0f;
+
+ // Row 0
+ out0.s0 = (w0.s0);
+ out0.s1 = (w0.s0 + w0.s1 + w0.s2) * 0.5f;
+ out0.s2 = (w0.s0 + w0.s2 - w0.s1) * 0.5f;
+ out0.s3 = (w0.s2);
+
+ // Row 1
+ out1.s0 = (w0.s0 + w1.s0 + w2.s0) * 0.5f;
+ out1.s1 = (w0.s0 + w1.s0 + w2.s0 + w0.s1 + w1.s1 + w2.s1 + w0.s2 + w1.s2 + w2.s2) * 0.25f;
+ out1.s2 = (w0.s0 + w1.s0 + w2.s0 + w0.s2 + w1.s2 + w2.s2 - w0.s1 - w1.s1 - w2.s1) * 0.25f;
+ out1.s3 = (w0.s2 + w1.s2 + w2.s2) * 0.5f;
+
+ // Row 2
+ out2.s0 = (w0.s0 + w2.s0 - w1.s0) * 0.5f;
+ out2.s1 = (w0.s0 + w2.s0 + w0.s1 + w2.s1 + w0.s2 + w2.s2 - w1.s0 - w1.s1 - w1.s2) * 0.25f;
+ out2.s2 = (w0.s0 + w2.s0 + w1.s1 + w0.s2 + w2.s2 - w1.s0 - w0.s1 - w2.s1 - w1.s2) * 0.25f;
+ out2.s3 = (w0.s2 + w2.s2 - w1.s2) * 0.5f;
+
+ // Row 3
+ out3.s0 = (w2.s0);
+ out3.s1 = (w2.s0 + w2.s1 + w2.s2) * 0.5f;
+ out3.s2 = (w2.s0 + w2.s2 - w2.s1) * 0.5f;
+ out3.s3 = (w2.s2);
+ int z = get_global_id(2);
+ int x0 = z / NUM_CHANNELS; // idx filter
+ int y0 = z % NUM_CHANNELS; // idx channel
+
+ // Get output address
+ __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x0 * dst_stride_x + y0 * dst_stride_y;
+
+ // Store the 16 values across the 16 channels
+ *(__global float *)(dst_addr + 0 * dst_stride_z) = out0.s0;
+ *(__global float *)(dst_addr + 1 * dst_stride_z) = out0.s1;
+ *(__global float *)(dst_addr + 2 * dst_stride_z) = out0.s2;
+ *(__global float *)(dst_addr + 3 * dst_stride_z) = out0.s3;
+ *(__global float *)(dst_addr + 4 * dst_stride_z) = out1.s0;
+ *(__global float *)(dst_addr + 5 * dst_stride_z) = out1.s1;
+ *(__global float *)(dst_addr + 6 * dst_stride_z) = out1.s2;
+ *(__global float *)(dst_addr + 7 * dst_stride_z) = out1.s3;
+ *(__global float *)(dst_addr + 8 * dst_stride_z) = out2.s0;
+ *(__global float *)(dst_addr + 9 * dst_stride_z) = out2.s1;
+ *(__global float *)(dst_addr + 10 * dst_stride_z) = out2.s2;
+ *(__global float *)(dst_addr + 11 * dst_stride_z) = out2.s3;
+ *(__global float *)(dst_addr + 12 * dst_stride_z) = out3.s0;
+ *(__global float *)(dst_addr + 13 * dst_stride_z) = out3.s1;
+ *(__global float *)(dst_addr + 14 * dst_stride_z) = out3.s2;
+ *(__global float *)(dst_addr + 15 * dst_stride_z) = out3.s3;
+}
+#endif // defined(NUM_CHANNELS)
+
+#if defined(NUM_TILES_X) && defined(PAD_LEFT) && defined(PAD_TOP)
/** This OpenCL kernel computes the input transform when the kernel size is 3x3 and the output tile is 2x2
*
* @note The number of tiles in the x axis must be passed at compile time using -DNUM_TILES_X (i.e.-DNUM_TILES_X=5).
@@ -205,13 +299,12 @@ __kernel void winograd_input_transform_2x2_3x3_stepz2_nchw(
vstore2(out32, 0, (__global float *)(dst_addr + 14 * dst_stride_z));
vstore2(out33, 0, (__global float *)(dst_addr + 15 * dst_stride_z));
}
-#endif //defined(NUM_TILES_X)
+#endif // defined(NUM_TILES_X) && defined(PAD_LEFT) && defined(PAD_TOP)
-#if defined(NUM_CHANNELS)
-
-/** This OpenCL kernel performs Winograd filter transform 3x3 when the data format is NCHW and the output tile is 2x2
+#if defined(NUM_TILES_X)
+/** This OpenCL kernel performs Winograd output transform when the output tile is 2x2, the filter size 3x3 and the data format is NCHW
*
- * @note The number of channels must be passed at compile time using -DNUM_CHANNELS: e.g. -DNUM_CHANNELS=64
+ * @note The number of tiles along the X direction must be passed at compile time using -DNUM_TILES_X: e.g. -DNUM_TILES_X=16
*
* @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)
@@ -220,8 +313,6 @@ __kernel void winograd_input_transform_2x2_3x3_stepz2_nchw(
* @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_stride_w Stride of the source tensor in W dimension (in bytes)
- * @param[in] src_step_w src_stride_w * number of elements along W 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)
@@ -232,72 +323,84 @@ __kernel void winograd_input_transform_2x2_3x3_stepz2_nchw(
* @param[in] src_step_z src_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
*/
-__kernel void winograd_filter_transform_2x2_3x3_nchw(
- TENSOR4D_DECLARATION(src),
- TENSOR3D_DECLARATION(dst))
+__kernel void winograd_output_transform_2x2_3x3_nchw(
+ TENSOR3D_DECLARATION(src),
+ TENSOR3D_DECLARATION(dst)
+#if defined(HAS_BIAS)
+ ,
+ VECTOR_DECLARATION(bias)
+#endif // defined(HAS_BIAS)
+)
{
- Tensor4D src = CONVERT_TO_TENSOR4D_STRUCT(src, NUM_CHANNELS);
-
- const __global uchar *src_addr = tensor4D_offset(&src, 0, 0, 0, 0);
-
- // Load the values from the input tensor
- float3 w0 = vload3(0, (__global float *)(src_addr + 0 * src_stride_y));
- float3 w1 = vload3(0, (__global float *)(src_addr + 1 * src_stride_y));
- float3 w2 = vload3(0, (__global float *)(src_addr + 2 * src_stride_y));
-
- // Transform the 3x3 tile in a 4x4 tile
- float4 out0 = 0.0f;
- float4 out1 = 0.0f;
- float4 out2 = 0.0f;
- float4 out3 = 0.0f;
-
- // Row 0
- out0.s0 = (w0.s0);
- out0.s1 = (w0.s0 + w0.s1 + w0.s2) * 0.5f;
- out0.s2 = (w0.s0 + w0.s2 - w0.s1) * 0.5f;
- out0.s3 = (w0.s2);
-
- // Row 1
- out1.s0 = (w0.s0 + w1.s0 + w2.s0) * 0.5f;
- out1.s1 = (w0.s0 + w1.s0 + w2.s0 + w0.s1 + w1.s1 + w2.s1 + w0.s2 + w1.s2 + w2.s2) * 0.25f;
- out1.s2 = (w0.s0 + w1.s0 + w2.s0 + w0.s2 + w1.s2 + w2.s2 - w0.s1 - w1.s1 - w2.s1) * 0.25f;
- out1.s3 = (w0.s2 + w1.s2 + w2.s2) * 0.5f;
-
- // Row 2
- out2.s0 = (w0.s0 + w2.s0 - w1.s0) * 0.5f;
- out2.s1 = (w0.s0 + w2.s0 + w0.s1 + w2.s1 + w0.s2 + w2.s2 - w1.s0 - w1.s1 - w1.s2) * 0.25f;
- out2.s2 = (w0.s0 + w2.s0 + w1.s1 + w0.s2 + w2.s2 - w1.s0 - w0.s1 - w2.s1 - w1.s2) * 0.25f;
- out2.s3 = (w0.s2 + w2.s2 - w1.s2) * 0.5f;
-
- // Row 3
- out3.s0 = (w2.s0);
- out3.s1 = (w2.s0 + w2.s1 + w2.s2) * 0.5f;
- out3.s2 = (w2.s0 + w2.s2 - w2.s1) * 0.5f;
- out3.s3 = (w2.s2);
-
- int z = get_global_id(2);
- int x0 = z / NUM_CHANNELS; // idx filter
- int y0 = z % NUM_CHANNELS; // idx channel
+ // Each thread stores a 2x2 tile
+ Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
+
+ const __global uchar *src_addr = tensor3D_offset(&src, 0, 0, 0);
+
+ // Load the values across the 16 channels to compose the 4x4 tile
+ float d00 = *((__global float *)(src_addr + 0 * src_stride_z));
+ float d01 = *((__global float *)(src_addr + 1 * src_stride_z));
+ float d02 = *((__global float *)(src_addr + 2 * src_stride_z));
+ float d03 = *((__global float *)(src_addr + 3 * src_stride_z));
+
+ float d10 = *((__global float *)(src_addr + 4 * src_stride_z));
+ float d11 = *((__global float *)(src_addr + 5 * src_stride_z));
+ float d12 = *((__global float *)(src_addr + 6 * src_stride_z));
+ float d13 = *((__global float *)(src_addr + 7 * src_stride_z));
+
+ float d20 = *((__global float *)(src_addr + 8 * src_stride_z));
+ float d21 = *((__global float *)(src_addr + 9 * src_stride_z));
+ float d22 = *((__global float *)(src_addr + 10 * src_stride_z));
+ float d23 = *((__global float *)(src_addr + 11 * src_stride_z));
+
+ float d30 = *((__global float *)(src_addr + 12 * src_stride_z));
+ float d31 = *((__global float *)(src_addr + 13 * src_stride_z));
+ float d32 = *((__global float *)(src_addr + 14 * src_stride_z));
+ float d33 = *((__global float *)(src_addr + 15 * src_stride_z));
+
+ // Compute the 2x2 output tile
+ float k0 = d01 + d11 + d21;
+ float k1 = d02 + d12 + d22;
+ float k2 = d11 - d21 - d31;
+ float k3 = d12 - d22 - d32;
+
+ // out00 = d00 + d10 + d20 + d01 + d11 + d21 + d02 + d12 + d22
+ // out01 = d01 + d11 + d21 - (d02 + d12 + d22) - (d03 + d13 + d23)
+ // out10 = d10 - d20 - d30 + (d11 - d21 - d31) + (d12 - d22 - d32)
+ // out11 = d11 - d21 - d31 - (d12 - d22 - d32) - (d13 - d23 - d33)
+
+ float out00 = d10;
+ float out01 = -d13;
+ float out10 = d10;
+ float out11 = -d13;
+
+ out00 += d00 + d20 + k0 + k1;
+ out01 += k0 - k1 - (d03 + d23);
+ out10 += -d20 - d30 + k2 + k3;
+ out11 += k2 - k3 + d23 + d33;
+
+ int y_in = get_global_id(1);
+ int x_out = (y_in % NUM_TILES_X) * 2;
+ int y_out = (y_in / NUM_TILES_X) * 2;
+ int z_out = get_global_id(0);
+
+#if defined(HAS_BIAS)
+ // Add bias
+ Vector bias = CONVERT_TO_VECTOR_STRUCT_NO_STEP(bias);
+
+ float b = (float) * ((__global float *)(vector_offset(&bias, z_out)));
+
+ out00 += (float)b;
+ out01 += (float)b;
+ out10 += (float)b;
+ out11 += (float)b;
+#endif // defined(HAS_BIAS)
// Get output address
- __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x0 * dst_stride_x + y0 * dst_stride_y;
+ __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x_out * dst_stride_x + y_out * dst_stride_y + z_out * dst_stride_z;
- // Store the 16 values across the 16 channels
- *(__global float *)(dst_addr + 0 * dst_stride_z) = out0.s0;
- *(__global float *)(dst_addr + 1 * dst_stride_z) = out0.s1;
- *(__global float *)(dst_addr + 2 * dst_stride_z) = out0.s2;
- *(__global float *)(dst_addr + 3 * dst_stride_z) = out0.s3;
- *(__global float *)(dst_addr + 4 * dst_stride_z) = out1.s0;
- *(__global float *)(dst_addr + 5 * dst_stride_z) = out1.s1;
- *(__global float *)(dst_addr + 6 * dst_stride_z) = out1.s2;
- *(__global float *)(dst_addr + 7 * dst_stride_z) = out1.s3;
- *(__global float *)(dst_addr + 8 * dst_stride_z) = out2.s0;
- *(__global float *)(dst_addr + 9 * dst_stride_z) = out2.s1;
- *(__global float *)(dst_addr + 10 * dst_stride_z) = out2.s2;
- *(__global float *)(dst_addr + 11 * dst_stride_z) = out2.s3;
- *(__global float *)(dst_addr + 12 * dst_stride_z) = out3.s0;
- *(__global float *)(dst_addr + 13 * dst_stride_z) = out3.s1;
- *(__global float *)(dst_addr + 14 * dst_stride_z) = out3.s2;
- *(__global float *)(dst_addr + 15 * dst_stride_z) = out3.s3;
+ // Store the 2x2 output tile
+ vstore2((float2)(out00, out01), 0, (__global float *)(dst_addr + 0 * dst_stride_y));
+ vstore2((float2)(out10, out11), 0, (__global float *)(dst_addr + 1 * dst_stride_y));
}
-#endif // defined(NUM_CHANNELS)
+#endif // defined(NUM_TILES_X)
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-12 08:24:57 +0000