COMPMID-477 - Optimized batched case in CLConvolutionLayer
Change-Id: I4ef18f49f1da0cb816aaa0762466b940792c15ed
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/84162
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index 019f3ea..2589bd1 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -168,16 +168,15 @@
{ "gemm_ma_f32", "gemm.cl" },
{ "gemm_ma_qs8", "gemm.cl" },
{ "gemm_ma_qs16", "gemm.cl" },
- { "gemm_mm_u8", "gemm.cl" },
- { "gemm_mm_f16", "gemm.cl" },
- { "gemm_mm_f32_midgard", "gemm.cl" },
- { "gemm_mm_f32_bifrost", "gemm.cl" },
+ { "gemm_mm_interleaved_transposed_u8", "gemm.cl" },
+ { "gemm_mm_interleaved_transposed_f16", "gemm.cl" },
+ { "gemm_mm_interleaved_transposed_f32_midgard", "gemm.cl" },
+ { "gemm_mm_interleaved_transposed_f32_bifrost", "gemm.cl" },
+ { "gemm_mm_interleaved_transposed_qs8", "gemm.cl" },
+ { "gemm_mm_interleaved_transposed_qs16", "gemm.cl" },
+ { "gemm_mm_floating_point", "gemm.cl" },
{ "gemm_mm_qs8", "gemm.cl" },
{ "gemm_mm_qs16", "gemm.cl" },
- { "gemm_vm_f16", "gemm.cl" },
- { "gemm_vm_f32", "gemm.cl" },
- { "gemm_vm_qs8", "gemm.cl" },
- { "gemm_vm_qs16", "gemm.cl" },
{ "gemm_lc_vm_f32", "gemm.cl" },
{ "gemm_transpose1x16", "gemm.cl" },
{ "gemm_transpose1x8", "gemm.cl" },
diff --git a/src/core/CL/cl_kernels/gemm.cl b/src/core/CL/cl_kernels/gemm.cl
index 00c73e7..35a2e47 100644
--- a/src/core/CL/cl_kernels/gemm.cl
+++ b/src/core/CL/cl_kernels/gemm.cl
@@ -48,10 +48,10 @@
uint x = get_global_id(0);
uint y = get_global_id(1);
- /* Compute address for Matrix B - source */
+ // Compute address for Matrix B - source
Image src = CONVERT_TO_IMAGE_STRUCT(src);
- /* Compute address for Matrix B transposed - destination. X and Y are swapped */
+ // Compute address for Matrix B transposed - destination. X and Y are swapped
uint dst_addr_in_bytes = y * 16 + ((x * dst_stride_y + dst_offset_first_element_in_bytes));
uint4 b0 = vload4(0, (__global uint *)src.ptr);
@@ -288,11 +288,11 @@
}
#endif /* DATA_TYPE */
-#ifdef WIDTH_MATRIX_B
+#ifdef COLS_B
/** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1)
* Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_8bit and @ref gemm_transpose1x16 before running the matrix multiplication
*
- * @attention The width of matrix B and the alpha's value need to be passed at compile time using -DWIDTH_MATRIX_B
+ * @attention The width of matrix B and the alpha's value need to be passed at compile time using -DCOLS_B
*
* @param[in] src0_ptr Pointer to the source matrix. Supported formats: U8
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -318,14 +318,14 @@
* @param[in] c_mult_int Multiplied with each element of the matrix C.
* @param[in] shift Number of bits to shift right the result.
*/
-__kernel void gemm_mm_u8(IMAGE_DECLARATION(src0),
- IMAGE_DECLARATION(src1),
- IMAGE_DECLARATION(dst),
- int a_offset,
- int b_offset,
- int c_offset,
- int c_mult_int,
- int shift)
+__kernel void gemm_mm_interleaved_transposed_u8(IMAGE_DECLARATION(src0),
+ IMAGE_DECLARATION(src1),
+ IMAGE_DECLARATION(dst),
+ int a_offset,
+ int b_offset,
+ int c_offset,
+ int c_mult_int,
+ int shift)
{
/* src_addr.s0 = address of matrix A */
/* src_addr.s1 = address of matrix B */
@@ -338,7 +338,7 @@
src_addr = src_addr + ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes));
/* Compute end row address for matrix B */
- int end_row_mtx_b = src_addr.s1 + WIDTH_MATRIX_B;
+ int end_row_mtx_b = src_addr.s1 + COLS_B;
/* Reset accumulators */
int16 c00 = 0.0f;
@@ -392,13 +392,13 @@
vstore16(convert_uchar16_sat(c20), 0, (__global uchar *)(offset(&dst, 0, 2)));
vstore16(convert_uchar16_sat(c30), 0, (__global uchar *)(offset(&dst, 0, 3)));
}
-#endif /* WIDTH_MATRIX_B */
+#endif /* COLS_B */
-#if defined(WIDTH_MATRIX_B) && defined(ALPHA)
+#if defined(COLS_B) && defined(ALPHA)
/** This OpenCL kernel is optimised for Midgard. It computes the matrix multiplication between matrix A (src0) and matrix B (src1)
* Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_32bit and @ref gemm_transpose1x4 before running the matrix multiplication
*
- * @attention The width of matrix B and the alpha's value need to be passed at compile time using -DWIDTH_MATRIX_B and -DALPHA
+ * @attention The width of matrix B and the alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -419,9 +419,9 @@
* @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
*/
-__kernel void gemm_mm_f32_midgard(IMAGE_DECLARATION(src0),
- IMAGE_DECLARATION(src1),
- IMAGE_DECLARATION(dst))
+__kernel void gemm_mm_interleaved_transposed_f32_midgard(IMAGE_DECLARATION(src0),
+ IMAGE_DECLARATION(src1),
+ IMAGE_DECLARATION(dst))
{
/* src_addr.s0 = address of matrix A */
/* src_addr.s1 = address of matrix B */
@@ -437,7 +437,7 @@
src_addr = src_addr >> 2;
/* Compute end row address for matrix B */
- int end_row_mtx_b = src_addr.s1 + WIDTH_MATRIX_B;
+ int end_row_mtx_b = src_addr.s1 + COLS_B;
/* Reset accumulators */
float4 c00 = 0.0f;
@@ -497,7 +497,7 @@
/** This OpenCL kernel is optimised for Bifrost. It computes the matrix multiplication between matrix A (src0) and matrix B (src1)
* Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_32bit and @ref gemm_transpose1x4 before running the matrix multiplication
*
- * @attention The width of matrix B and the alpha's value need to be passed at compile time using -DWIDTH_MATRIX_B and -DALPHA
+ * @attention The width of matrix B and the alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -518,9 +518,9 @@
* @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
*/
-__kernel void gemm_mm_f32_bifrost(IMAGE_DECLARATION(src0),
- IMAGE_DECLARATION(src1),
- IMAGE_DECLARATION(dst))
+__kernel void gemm_mm_interleaved_transposed_f32_bifrost(IMAGE_DECLARATION(src0),
+ IMAGE_DECLARATION(src1),
+ IMAGE_DECLARATION(dst))
{
// src_addr_a = address of matrix A
// src_addr_b = address of matrix B
@@ -528,7 +528,7 @@
__global float *src_addr_b = (__global float *)(src1_ptr + get_global_id(0) * src1_stride_y + src1_offset_first_element_in_bytes);
// Compute end row address for matrix B
- __global float *src_end_addr_b = src_addr_b + WIDTH_MATRIX_B;
+ __global float *src_end_addr_b = src_addr_b + COLS_B;
// Reset accumulators
float c00 = 0.0f;
@@ -707,7 +707,7 @@
/** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1)
* Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_16bit and @ref gemm_transpose1x8 before running the matrix multiplication
*
- * @attention The width of matrix B and the alpha's value need to be passed at compile time using -DWIDTH_MATRIX_B and -DALPHA
+ * @attention The width of matrix B and the alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -728,9 +728,9 @@
* @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
*/
-__kernel void gemm_mm_f16(IMAGE_DECLARATION(src0),
- IMAGE_DECLARATION(src1),
- IMAGE_DECLARATION(dst))
+__kernel void gemm_mm_interleaved_transposed_f16(IMAGE_DECLARATION(src0),
+ IMAGE_DECLARATION(src1),
+ IMAGE_DECLARATION(dst))
{
/* src_addr.s0 = address of matrix A */
/* src_addr.s1 = address of matrix B */
@@ -746,7 +746,7 @@
src_addr = src_addr >> 1;
/* Compute end row address for matrix B */
- int end_row_mtx_b = src_addr.s1 + WIDTH_MATRIX_B;
+ int end_row_mtx_b = src_addr.s1 + COLS_B;
/* Reset accumulators */
half8 c00 = 0.0f;
@@ -807,7 +807,7 @@
/** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1) in 8 bit fixed point precision
* Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_8bit and @ref gemm_transpose1x16 before running the matrix multiplication
*
- * @attention The width of matrix B, the alpha's value and fixed point position need to be passed at compile time using -DWIDTH_MATRIX_B -DALPHA and -DFIXED_POINT_POSITION
+ * @attention The width of matrix B, the alpha's value and fixed point position need to be passed at compile time using -DCOLS_B -DALPHA and -DFIXED_POINT_POSITION
*
* @note: ALPHA must be passed in 8 bit fixed point format
*
@@ -830,9 +830,9 @@
* @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
*/
-__kernel void gemm_mm_qs8(IMAGE_DECLARATION(src0),
- IMAGE_DECLARATION(src1),
- IMAGE_DECLARATION(dst))
+__kernel void gemm_mm_interleaved_transposed_qs8(IMAGE_DECLARATION(src0),
+ IMAGE_DECLARATION(src1),
+ IMAGE_DECLARATION(dst))
{
/* src_addr.s0 = address of matrix A */
/* src_addr.s1 = address of matrix B */
@@ -845,7 +845,7 @@
src_addr = src_addr + ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes));
/* Compute end row address for matrix B */
- int end_row_mtx_b = src_addr.s1 + WIDTH_MATRIX_B;
+ int end_row_mtx_b = src_addr.s1 + COLS_B;
/* Reset accumulators */
short8 c00 = 0.0f;
@@ -899,7 +899,7 @@
/** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1) in 16 bit fixed point precision
* Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_16bit and @ref gemm_transpose1x8 before running the matrix multiplication
*
- * @attention The width of matrix B, the alpha's value and fixed point position need to be passed at compile time using -DWIDTH_MATRIX_B -DALPHA and -DFIXED_POINT_POSITION
+ * @attention The width of matrix B, the alpha's value and fixed point position need to be passed at compile time using -DCOLS_B -DALPHA and -DFIXED_POINT_POSITION
*
* @note: ALPHA must be passed in 16 bit fixed point format
*
@@ -922,9 +922,9 @@
* @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
*/
-__kernel void gemm_mm_qs16(IMAGE_DECLARATION(src0),
- IMAGE_DECLARATION(src1),
- IMAGE_DECLARATION(dst))
+__kernel void gemm_mm_interleaved_transposed_qs16(IMAGE_DECLARATION(src0),
+ IMAGE_DECLARATION(src1),
+ IMAGE_DECLARATION(dst))
{
/* src_addr.s0 = address of matrix A */
/* src_addr.s1 = address of matrix B */
@@ -940,7 +940,7 @@
src_addr = src_addr >> 1;
/* Compute end row address for matrix B */
- int end_row_mtx_b = src_addr.s1 + WIDTH_MATRIX_B;
+ int end_row_mtx_b = src_addr.s1 + COLS_B;
/* Reset accumulators */
int8 c00 = 0.0f;
@@ -983,14 +983,17 @@
}
#endif // defined(FIXED_POINT_POSITION)
-#ifdef WIDTH_VECTOR_A
-/** This OpenCL kernel computes the vector by matrix multiplication between the vector A (src0) and matrix B (src1)
+#if defined(COLS_A) && defined(NUM_ELEMS_PROCESSED_PER_THREAD_X) && (NUM_ELEMS_PROCESSED_PER_THREAD_Y)
+#if defined(DATA_TYPE)
+#define VECTOR_TYPE VEC_DATA_TYPE(DATA_TYPE, NUM_ELEMS_PROCESSED_PER_THREAD_X)
+/** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not beed reshaped
*
- * @attention The width of vector A, the width of matrix B and the alpha's value need to be passed at compile time using -DWIDTH_VECTOR_A -DWIDTH_MATRIX_B and -DALPHA
+ * @note This OpenCL kernel works with floating point data types (F16/F32)
+ * @note The floating point data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=float)
+ * @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y
+ * @note The width of matrix A and the alpha's value need to be passed at compile time using -DCOLS_A and -DALPHA
*
- * @attention The input vector A and matrix B must not be reshaped
- *
- * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F32
+ * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16/F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] src0_stride_y Stride of the source matrix in Y dimension (in bytes)
@@ -1009,127 +1012,136 @@
* @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
*/
-__kernel void gemm_vm_f32(IMAGE_DECLARATION(src0),
- IMAGE_DECLARATION(src1),
- IMAGE_DECLARATION(dst))
+__kernel void gemm_mm_floating_point(IMAGE_DECLARATION(src0),
+ IMAGE_DECLARATION(src1),
+ IMAGE_DECLARATION(dst))
{
- int idx = get_global_id(0) * 4;
+ int idx = get_global_id(0) * NUM_ELEMS_PROCESSED_PER_THREAD_X;
- /* Compute the address for the vector A and matrix B */
+ // Compute starting address for matrix A and Matrix B
int2 src_addr = ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes));
- src_addr.s1 += idx * sizeof(float);
- int end_row_vec_a = src_addr.s0 + (WIDTH_VECTOR_A * sizeof(float));
+ // Update address for the matrix A
+ src_addr.s0 += get_global_id(1) * src0_stride_y * NUM_ELEMS_PROCESSED_PER_THREAD_Y;
- float4 acc = 0.0f;
+ // Update address for the matrix B
+ src_addr.s1 += idx * sizeof(DATA_TYPE);
- for(; src_addr.s0 <= (end_row_vec_a - 2 * sizeof(float)); src_addr += (int2)(2 * sizeof(float), 2 * src1_stride_y))
+ int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(DATA_TYPE));
+
+ VECTOR_TYPE acc0 = 0.0f;
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ VECTOR_TYPE acc1 = 0.0f;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ VECTOR_TYPE acc2 = 0.0f;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ VECTOR_TYPE acc3 = 0.0f;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+
+ for(; src_addr.s0 <= (end_row_vec_a - 2 * sizeof(DATA_TYPE)); src_addr += (int2)(2 * sizeof(DATA_TYPE), 2 * src1_stride_y))
{
- float2 a0 = vload2(0, (__global float *)(src0_ptr + src_addr.s0));
- float4 b0 = vload4(0, (__global float *)(src1_ptr + src_addr.s1));
- float4 b1 = vload4(0, (__global float *)(src1_ptr + src_addr.s1 + src1_stride_y));
+ // Load values from matrix A
+ VEC_DATA_TYPE(DATA_TYPE, 2)
+ a0 = vload2(0, (__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y));
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ VEC_DATA_TYPE(DATA_TYPE, 2)
+ a1 = vload2(0, (__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 1 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ VEC_DATA_TYPE(DATA_TYPE, 2)
+ a2 = vload2(0, (__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 2 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ VEC_DATA_TYPE(DATA_TYPE, 2)
+ a3 = vload2(0, (__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ // Load values from matrix B
+ VECTOR_TYPE b0 = VLOAD(NUM_ELEMS_PROCESSED_PER_THREAD_X)(0, (__global DATA_TYPE *)(src1_ptr + src_addr.s1));
+ VECTOR_TYPE b1 = VLOAD(NUM_ELEMS_PROCESSED_PER_THREAD_X)(0, (__global DATA_TYPE *)(src1_ptr + src_addr.s1 + src1_stride_y));
- acc += b0 * (float4)a0.s0;
- acc += b1 * (float4)a0.s1;
+ // Accumulate
+ acc0 += b0 * (VECTOR_TYPE)a0.s0;
+ acc0 += b1 * (VECTOR_TYPE)a0.s1;
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ acc1 += b0 * (VECTOR_TYPE)a1.s0;
+ acc1 += b1 * (VECTOR_TYPE)a1.s1;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ acc2 += b0 * (VECTOR_TYPE)a2.s0;
+ acc2 += b1 * (VECTOR_TYPE)a2.s1;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ acc3 += b0 * (VECTOR_TYPE)a3.s0;
+ acc3 += b1 * (VECTOR_TYPE)a3.s1;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
}
- for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(sizeof(float), src1_stride_y))
+ for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(sizeof(DATA_TYPE), src1_stride_y))
{
- float a0 = *((__global float *)(src0_ptr + src_addr.s0));
- float4 b0 = vload4(0, (__global float *)(src1_ptr + src_addr.s1));
+ // Load values from matrix A
+ DATA_TYPE a0 = *((__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y));
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ DATA_TYPE a1 = *((__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 1 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ DATA_TYPE a2 = *((__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 2 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ DATA_TYPE a3 = *((__global DATA_TYPE *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ // Load values from matrix B
+ VECTOR_TYPE b0 = VLOAD(NUM_ELEMS_PROCESSED_PER_THREAD_X)(0, (__global DATA_TYPE *)(src1_ptr + src_addr.s1));
- acc += b0 * (float4)a0;
+ // Accumulate
+ acc0 += b0 * (VECTOR_TYPE)a0;
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ acc1 += b0 * (VECTOR_TYPE)a1;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ acc2 += b0 * (VECTOR_TYPE)a2;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ acc3 += b0 * (VECTOR_TYPE)a3;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
}
- /* Compute destination address */
+ // Compute destination address
Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
- /* Multiply by the weight of vector-matrix product */
- acc = acc * (float4)ALPHA;
-
- vstore4(acc, 0, (__global float *)(offset(&dst, 0, 0)));
+ // Multiply by the weight of matrix-matrix product and store the result
+ acc0 = acc0 * (VECTOR_TYPE)ALPHA;
+ VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X)
+ (acc0, 0, (__global DATA_TYPE *)(offset(&dst, 0, 0)));
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ acc1 = acc1 * (VECTOR_TYPE)ALPHA;
+ VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X)
+ (acc1, 0, (__global DATA_TYPE *)(offset(&dst, 0, 1)));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ acc2 = acc2 * (VECTOR_TYPE)ALPHA;
+ VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X)
+ (acc2, 0, (__global DATA_TYPE *)(offset(&dst, 0, 2)));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ acc3 = acc3 * (VECTOR_TYPE)ALPHA;
+ VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X)
+ (acc3, 0, (__global DATA_TYPE *)(offset(&dst, 0, 3)));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
}
-
-/** This OpenCL kernel computes the vector by matrix multiplication between the vector A (src0) and matrix B (src1)
- *
- * @attention The width of vector A, the width of matrix B and the alpha's value need to be passed at compile time using -DWIDTH_VECTOR_A -DWIDTH_MATRIX_B and -DALPHA
- *
- * @attention The input vector A and matrix B must not be reshaped
- *
- * @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16
- * @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
- * @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] src0_stride_y Stride of the source matrix in Y dimension (in bytes)
- * @param[in] src0_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in] src0_offset_first_element_in_bytes The offset of the first element in the source matrix
- * @param[in] src1_ptr Pointer to the source matrix. Supported data types: same as @p src0_ptr
- * @param[in] src1_stride_x Stride of the source matrix in X dimension (in bytes)
- * @param[in] src1_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes)
- * @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix
- * @param[out] dst_ptr Pointer to the destination matrix Supported data types: same as @p src0_ptr
- * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes)
- * @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes)
- * @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
- */
-__kernel void gemm_vm_f16(IMAGE_DECLARATION(src0),
- IMAGE_DECLARATION(src1),
- IMAGE_DECLARATION(dst))
-{
- int idx = get_global_id(0) * 8;
-
- /* Compute the address for the vector A and matrix B */
- int2 src_addr = ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes));
- src_addr.s1 += idx * sizeof(half);
-
- int end_row_vec_a = src_addr.s0 + (WIDTH_VECTOR_A * sizeof(half));
-
- half8 acc = 0.0f;
-
- for(; src_addr.s0 <= (end_row_vec_a - 4 * sizeof(half)); src_addr += (int2)(4 * sizeof(half), 4 * src1_stride_y))
- {
- half4 a0 = vload4(0, (__global half *)(src0_ptr + src_addr.s0));
- half8 b0 = vload8(0, (__global half *)(src1_ptr + src_addr.s1 + 0 * src1_stride_y));
- half8 b1 = vload8(0, (__global half *)(src1_ptr + src_addr.s1 + 1 * src1_stride_y));
- half8 b2 = vload8(0, (__global half *)(src1_ptr + src_addr.s1 + 2 * src1_stride_y));
- half8 b3 = vload8(0, (__global half *)(src1_ptr + src_addr.s1 + 3 * src1_stride_y));
-
- acc += b0 * (half8)a0.s0;
- acc += b1 * (half8)a0.s1;
- acc += b2 * (half8)a0.s2;
- acc += b3 * (half8)a0.s3;
- }
-
- for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(sizeof(half), src1_stride_y))
- {
- half a0 = *((__global half *)(src0_ptr + src_addr.s0));
- half8 b0 = vload8(0, (__global half *)(src1_ptr + src_addr.s1));
-
- acc += b0 * (half8)a0;
- }
-
- /* Compute destination address */
- Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
-
- /* Multiply by the weight of vector-matrix product */
- acc = acc * (half8)ALPHA;
-
- vstore8(acc, 0, (__global half *)(offset(&dst, 0, 0)));
-}
+#endif // defined(DATA_TYPE)
#ifdef FIXED_POINT_POSITION
-/** This OpenCL kernel computes the vector by matrix multiplication between the vector A (src0) and matrix B (src1) in 8 bit fixed point
+/** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not beed reshaped
*
- * @attention The width of vector A, the width of matrix B, the alpha's value and the fixed point position need to be passed at compile time using -DWIDTH_VECTOR_A -DWIDTH_MATRIX_B, -DALPHA and -DFIXED_POINT_POSITION
+ * @note This OpenCL kernel works with fixed point data types QS8
+ * @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y
+ * @note The width of matrix A, the number of elements processed per thread along the Y direction and the alpha's value need to be passed at compile time using -DCOLS_A, -DNUM_ELEMS_PROCESSED_PER_THREAD_Y and -DALPHA
+ * @note The fixed point position need to be passed at compile time using -DFIXED_POINT_POSITION
+ * @note The alpha value must be passed in 8 bit fixed point format using -DALPHA
*
- * @attention The input vector A and matrix B must not be reshaped
- *
- * @note: ALPHA must be passed in 8 bit fixed point format
- *
- * @param[in] src0_ptr Pointer to the source matrix. Supported data types: QS8
+ * @param[in] src0_ptr Pointer to the source matrix. Supported data types: QS8/QS16
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] src0_stride_y Stride of the source matrix in Y dimension (in bytes)
@@ -1148,72 +1160,143 @@
* @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
*/
-__kernel void gemm_vm_qs8(IMAGE_DECLARATION(src0),
+__kernel void gemm_mm_qs8(IMAGE_DECLARATION(src0),
IMAGE_DECLARATION(src1),
IMAGE_DECLARATION(dst))
{
- int idx = get_global_id(0) * 16;
+ int idx = get_global_id(0) * NUM_ELEMS_PROCESSED_PER_THREAD_X;
- /* Compute the address for the vector A and matrix B */
+ // Compute starting address for matrix A and Matrix B
int2 src_addr = ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes));
- src_addr.s1 += idx;
- int end_row_vec_a = src_addr.s0 + WIDTH_VECTOR_A;
+ // Update address for the matrix A
+ src_addr.s0 += get_global_id(1) * src0_stride_y * NUM_ELEMS_PROCESSED_PER_THREAD_Y;
- short8 acc0 = 0;
- short8 acc1 = 0;
+ // Update address for the matrix B
+ src_addr.s1 += idx * sizeof(char);
- /* This for loop performs 4 accumulations per iteration */
- for(; src_addr.s0 <= (end_row_vec_a - 4); src_addr += (int2)(4, 4 * src1_stride_y))
+ int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(char));
+
+ short8 acc00 = 0;
+ short8 acc01 = 0;
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ short8 acc10 = 0;
+ short8 acc11 = 0;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ short8 acc20 = 0;
+ short8 acc21 = 0;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ short8 acc30 = 0;
+ short8 acc31 = 0;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+
+ // This for loop performs 4 accumulations per iteration
+ for(; src_addr.s0 <= (end_row_vec_a - 2); src_addr += (int2)(2, 2 * src1_stride_y))
{
- char4 a0 = vload4(0, (__global char *)(src0_ptr + src_addr.s0));
+ char2 a0 = vload2(0, (__global char *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y));
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ char2 a1 = vload2(0, (__global char *)(src0_ptr + src_addr.s0 + 1 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ char2 a2 = vload2(0, (__global char *)(src0_ptr + src_addr.s0 + 2 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ char2 a3 = vload2(0, (__global char *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
char16 b0 = vload16(0, (__global char *)(src1_ptr + src_addr.s1 + 0 * src1_stride_y));
char16 b1 = vload16(0, (__global char *)(src1_ptr + src_addr.s1 + 1 * src1_stride_y));
- char16 b2 = vload16(0, (__global char *)(src1_ptr + src_addr.s1 + 2 * src1_stride_y));
- char16 b3 = vload16(0, (__global char *)(src1_ptr + src_addr.s1 + 3 * src1_stride_y));
- acc0 = mlal_sat_qs8x8(acc0, (char8)a0.s0, b0.s01234567, FIXED_POINT_POSITION);
- acc0 = mlal_sat_qs8x8(acc0, (char8)a0.s1, b1.s01234567, FIXED_POINT_POSITION);
- acc0 = mlal_sat_qs8x8(acc0, (char8)a0.s2, b2.s01234567, FIXED_POINT_POSITION);
- acc0 = mlal_sat_qs8x8(acc0, (char8)a0.s3, b3.s01234567, FIXED_POINT_POSITION);
-
- acc1 = mlal_sat_qs8x8(acc1, (char8)a0.s0, b0.s89ABCDEF, FIXED_POINT_POSITION);
- acc1 = mlal_sat_qs8x8(acc1, (char8)a0.s1, b1.s89ABCDEF, FIXED_POINT_POSITION);
- acc1 = mlal_sat_qs8x8(acc1, (char8)a0.s2, b2.s89ABCDEF, FIXED_POINT_POSITION);
- acc1 = mlal_sat_qs8x8(acc1, (char8)a0.s3, b3.s89ABCDEF, FIXED_POINT_POSITION);
+ acc00 = mlal_sat_qs8x8(acc00, (char8)a0.s0, b0.s01234567, FIXED_POINT_POSITION);
+ acc00 = mlal_sat_qs8x8(acc00, (char8)a0.s1, b1.s01234567, FIXED_POINT_POSITION);
+ acc01 = mlal_sat_qs8x8(acc01, (char8)a0.s0, b0.s89ABCDEF, FIXED_POINT_POSITION);
+ acc01 = mlal_sat_qs8x8(acc01, (char8)a0.s1, b1.s89ABCDEF, FIXED_POINT_POSITION);
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ acc10 = mlal_sat_qs8x8(acc10, (char8)a1.s0, b0.s01234567, FIXED_POINT_POSITION);
+ acc10 = mlal_sat_qs8x8(acc10, (char8)a1.s1, b1.s01234567, FIXED_POINT_POSITION);
+ acc11 = mlal_sat_qs8x8(acc11, (char8)a1.s0, b0.s89ABCDEF, FIXED_POINT_POSITION);
+ acc11 = mlal_sat_qs8x8(acc11, (char8)a1.s1, b1.s89ABCDEF, FIXED_POINT_POSITION);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ acc20 = mlal_sat_qs8x8(acc20, (char8)a2.s0, b0.s01234567, FIXED_POINT_POSITION);
+ acc20 = mlal_sat_qs8x8(acc20, (char8)a2.s1, b1.s01234567, FIXED_POINT_POSITION);
+ acc21 = mlal_sat_qs8x8(acc21, (char8)a2.s0, b0.s89ABCDEF, FIXED_POINT_POSITION);
+ acc21 = mlal_sat_qs8x8(acc21, (char8)a2.s1, b1.s89ABCDEF, FIXED_POINT_POSITION);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ acc30 = mlal_sat_qs8x8(acc30, (char8)a3.s0, b0.s01234567, FIXED_POINT_POSITION);
+ acc30 = mlal_sat_qs8x8(acc30, (char8)a3.s1, b1.s01234567, FIXED_POINT_POSITION);
+ acc31 = mlal_sat_qs8x8(acc31, (char8)a3.s0, b0.s89ABCDEF, FIXED_POINT_POSITION);
+ acc31 = mlal_sat_qs8x8(acc31, (char8)a3.s1, b1.s89ABCDEF, FIXED_POINT_POSITION);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
}
- /* Left-over accumulations */
+ // Left-over accumulations
for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(1, src1_stride_y))
{
- char a0 = *((__global char *)(src0_ptr + src_addr.s0));
+ char a0 = *((__global char *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y));
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ char a1 = *((__global char *)(src0_ptr + src_addr.s0 + 1 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ char a2 = *((__global char *)(src0_ptr + src_addr.s0 + 2 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ char a3 = *((__global char *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
char16 b0 = vload16(0, (__global char *)(src1_ptr + src_addr.s1));
- acc0 = mlal_sat_qs8x8(acc0, (char8)a0, b0.s01234567, FIXED_POINT_POSITION);
- acc1 = mlal_sat_qs8x8(acc1, (char8)a0, b0.s89ABCDEF, FIXED_POINT_POSITION);
+ acc00 = mlal_sat_qs8x8(acc00, (char8)a0, b0.s01234567, FIXED_POINT_POSITION);
+ acc01 = mlal_sat_qs8x8(acc01, (char8)a0, b0.s89ABCDEF, FIXED_POINT_POSITION);
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ acc10 = mlal_sat_qs8x8(acc10, (char8)a1, b0.s01234567, FIXED_POINT_POSITION);
+ acc11 = mlal_sat_qs8x8(acc11, (char8)a1, b0.s89ABCDEF, FIXED_POINT_POSITION);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ acc20 = mlal_sat_qs8x8(acc20, (char8)a2, b0.s01234567, FIXED_POINT_POSITION);
+ acc21 = mlal_sat_qs8x8(acc21, (char8)a2, b0.s89ABCDEF, FIXED_POINT_POSITION);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ acc30 = mlal_sat_qs8x8(acc30, (char8)a3, b0.s01234567, FIXED_POINT_POSITION);
+ acc31 = mlal_sat_qs8x8(acc31, (char8)a3, b0.s89ABCDEF, FIXED_POINT_POSITION);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
}
- /* Compute destination address */
+ // Compute destination address
Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
- /* Multiply by the weight of matrix product */
- char16 acc_qs8 = convert_char16_sat((short16)(acc0, acc1));
-
+ // Multiply by the weight of matrix product and store the result
+ char16 acc_qs8;
+ acc_qs8 = convert_char16_sat((short16)(acc00, acc01));
acc_qs8 = mul_sat_qs8x16(acc_qs8, (char16)ALPHA, FIXED_POINT_POSITION);
-
- /* Store 16 values */
vstore16(acc_qs8, 0, (__global char *)(offset(&dst, 0, 0)));
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ acc_qs8 = convert_char16_sat((short16)(acc10, acc11));
+ acc_qs8 = mul_sat_qs8x16(acc_qs8, (char16)ALPHA, FIXED_POINT_POSITION);
+ vstore16(acc_qs8, 0, (__global char *)(offset(&dst, 0, 1)));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ acc_qs8 = convert_char16_sat((short16)(acc20, acc21));
+ acc_qs8 = mul_sat_qs8x16(acc_qs8, (char16)ALPHA, FIXED_POINT_POSITION);
+ vstore16(acc_qs8, 0, (__global char *)(offset(&dst, 0, 2)));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ acc_qs8 = convert_char16_sat((short16)(acc30, acc31));
+ acc_qs8 = mul_sat_qs8x16(acc_qs8, (char16)ALPHA, FIXED_POINT_POSITION);
+ vstore16(acc_qs8, 0, (__global char *)(offset(&dst, 0, 3)));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
}
-/** This OpenCL kernel computes the vector by matrix multiplication between the vector A (src0) and matrix B (src1) in 16 bit fixed point
+/** This OpenCL kernel computes the matrix by matrix multiplication between the matrix A (src0) and matrix B (src1) in case both matrices have not beed reshaped
*
- * @attention The width of vector A, the width of matrix B, the alpha's value and the fixed point position need to be passed at compile time using -DWIDTH_VECTOR_A -DWIDTH_MATRIX_B, -DALPHA and -DFIXED_POINT_POSITION
+ * @note This OpenCL kernel works with fixed point data types QS16
+ * @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y
+ * @note The width of matrix A, the number of elements processed per thread along the Y direction and the alpha's value need to be passed at compile time using -DCOLS_A, -DNUM_ELEMS_PROCESSED_PER_THREAD_Y and -DALPHA
+ * @note The fixed point position need to be passed at compile time using -DFIXED_POINT_POSITION
+ * @note The alpha value must be passed in 16 bit fixed point format using -DALPHA
*
- * @attention The input vector A and matrix B must not be reshaped
- *
- * @note: ALPHA must be passed in 16 bit fixed point format
- *
- * @param[in] src0_ptr Pointer to the source matrix. Supported data types: QS16
+ * @param[in] src0_ptr Pointer to the source matrix. Supported data types: QS8/QS16
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
* @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] src0_stride_y Stride of the source matrix in Y dimension (in bytes)
@@ -1232,59 +1315,120 @@
* @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
*/
-__kernel void gemm_vm_qs16(IMAGE_DECLARATION(src0),
+__kernel void gemm_mm_qs16(IMAGE_DECLARATION(src0),
IMAGE_DECLARATION(src1),
IMAGE_DECLARATION(dst))
{
- int idx = get_global_id(0) * 8;
+ int idx = get_global_id(0) * NUM_ELEMS_PROCESSED_PER_THREAD_X;
- /* Compute the address for the vector A and matrix B */
+ // Compute starting address for matrix A and Matrix B
int2 src_addr = ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes));
+
+ // Update address for the matrix A
+ src_addr.s0 += get_global_id(1) * src0_stride_y * NUM_ELEMS_PROCESSED_PER_THREAD_Y;
+
+ // Update address for the matrix B
src_addr.s1 += idx * sizeof(short);
- int end_row_vec_a = src_addr.s0 + (WIDTH_VECTOR_A * sizeof(short));
+ int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(short));
- /* Reset accumulator */
int8 acc0 = 0;
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ int8 acc1 = 0;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ int8 acc2 = 0;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ int8 acc3 = 0;
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
- /* This for loop performs 4 accumulations per iteration */
- for(; src_addr.s0 <= (end_row_vec_a - 4 * sizeof(short)); src_addr += (int2)(4 * sizeof(short), 4 * src1_stride_y))
+ // This for loop performs 4 accumulations per iteration
+ for(; src_addr.s0 <= (end_row_vec_a - 2 * sizeof(short)); src_addr += (int2)(2 * sizeof(short), 2 * src1_stride_y))
{
- short4 a0 = vload4(0, (__global short *)(src0_ptr + src_addr.s0));
+ short2 a0 = vload2(0, (__global short *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y));
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ short2 a1 = vload2(0, (__global short *)(src0_ptr + src_addr.s0 + 1 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ short2 a2 = vload2(0, (__global short *)(src0_ptr + src_addr.s0 + 2 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ short2 a3 = vload2(0, (__global short *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
short8 b0 = vload8(0, (__global short *)(src1_ptr + src_addr.s1 + 0 * src1_stride_y));
short8 b1 = vload8(0, (__global short *)(src1_ptr + src_addr.s1 + 1 * src1_stride_y));
- short8 b2 = vload8(0, (__global short *)(src1_ptr + src_addr.s1 + 2 * src1_stride_y));
- short8 b3 = vload8(0, (__global short *)(src1_ptr + src_addr.s1 + 3 * src1_stride_y));
acc0 = mlal_sat_qs16x8(acc0, (short8)a0.s0, b0, FIXED_POINT_POSITION);
acc0 = mlal_sat_qs16x8(acc0, (short8)a0.s1, b1, FIXED_POINT_POSITION);
- acc0 = mlal_sat_qs16x8(acc0, (short8)a0.s2, b2, FIXED_POINT_POSITION);
- acc0 = mlal_sat_qs16x8(acc0, (short8)a0.s3, b3, FIXED_POINT_POSITION);
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ acc1 = mlal_sat_qs16x8(acc1, (short8)a1.s0, b0, FIXED_POINT_POSITION);
+ acc1 = mlal_sat_qs16x8(acc1, (short8)a1.s1, b1, FIXED_POINT_POSITION);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ acc2 = mlal_sat_qs16x8(acc2, (short8)a2.s0, b0, FIXED_POINT_POSITION);
+ acc2 = mlal_sat_qs16x8(acc2, (short8)a2.s1, b1, FIXED_POINT_POSITION);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ acc3 = mlal_sat_qs16x8(acc3, (short8)a3.s0, b0, FIXED_POINT_POSITION);
+ acc3 = mlal_sat_qs16x8(acc3, (short8)a3.s1, b1, FIXED_POINT_POSITION);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
}
- /* Left-over accumulations */
+ // Left-over accumulations
for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(sizeof(short), src1_stride_y))
{
- short a0 = *((__global short *)(src0_ptr + src_addr.s0));
+ short a0 = *((__global short *)(src0_ptr + src_addr.s0 + 0 * src0_stride_y));
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ short a1 = *((__global short *)(src0_ptr + src_addr.s0 + 1 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ short a2 = *((__global short *)(src0_ptr + src_addr.s0 + 2 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ short a3 = *((__global short *)(src0_ptr + src_addr.s0 + 3 * src0_stride_y));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
short8 b0 = vload8(0, (__global short *)(src1_ptr + src_addr.s1));
acc0 = mlal_sat_qs16x8(acc0, (short8)a0, b0, FIXED_POINT_POSITION);
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ acc1 = mlal_sat_qs16x8(acc1, (short8)a1, b0, FIXED_POINT_POSITION);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ acc2 = mlal_sat_qs16x8(acc2, (short8)a2, b0, FIXED_POINT_POSITION);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ acc3 = mlal_sat_qs16x8(acc3, (short8)a3, b0, FIXED_POINT_POSITION);
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
}
- /* Compute destination address */
+ // Compute destination address
Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
- /* Multiply by the weight of matrix product */
- short8 acc_qs16 = convert_short8_sat(acc0);
-
+ // Multiply by the weight of matrix product and store the result
+ short8 acc_qs16;
+ acc_qs16 = convert_short8_sat(acc0);
acc_qs16 = mul_sat_qs16x8(acc_qs16, (short8)ALPHA, FIXED_POINT_POSITION);
-
- /* Store 8 values */
vstore8(acc_qs16, 0, (__global short *)(offset(&dst, 0, 0)));
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+ acc_qs16 = convert_short8_sat(acc1);
+ acc_qs16 = mul_sat_qs16x8(acc_qs16, (short8)ALPHA, FIXED_POINT_POSITION);
+ vstore8(acc_qs16, 0, (__global short *)(offset(&dst, 0, 1)));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+ acc_qs16 = convert_short8_sat(acc2);
+ acc_qs16 = mul_sat_qs16x8(acc_qs16, (short8)ALPHA, FIXED_POINT_POSITION);
+ vstore8(acc_qs16, 0, (__global short *)(offset(&dst, 0, 2)));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2
+#if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
+ acc_qs16 = convert_short8_sat(acc3);
+ acc_qs16 = mul_sat_qs16x8(acc_qs16, (short8)ALPHA, FIXED_POINT_POSITION);
+ vstore8(acc_qs16, 0, (__global short *)(offset(&dst, 0, 3)));
+#endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3
}
-#endif /* defined(FIXED_POINT_POSITION) */
-#endif /* defined(WIDTH_VECTOR_A) */
-#endif /* defined(WIDTH_MATRIX_B) && defined(ALPHA) */
+#endif // defined(FIXED_POINT_POSITION)
+#endif // defined(COLS_A) && defined(NUM_ELEMS_PROCESSED_PER_THREAD_X) && (NUM_ELEMS_PROCESSED_PER_THREAD_Y)
+#endif // defined(COLS_B) && defined(ALPHA)
#ifdef BETA
/** This OpenCL kernel performs the in-place matrix addition between 2 matrices taking into account that the second matrix might be weighted by a scalar value beta:
@@ -1508,4 +1652,4 @@
vstore4(acc, 0, (__global float *)(offset(&dst, 0, 0)));
}
-#endif /* WIDTH_VECTOR_A */
+#endif /* WIDTH_VECTOR_A */
\ No newline at end of file
diff --git a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp
index ce68c1f..ef572cf 100644
--- a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp
@@ -64,8 +64,8 @@
_output = output;
// Create kernel and set static arguments
- std::set<std::string> build_opts = { ("-DWIDTH_MATRIX_B=" + support::cpp11::to_string(input1->info()->dimension(0))) };
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_mm_u8", build_opts));
+ std::set<std::string> build_opts = { ("-DCOLS_B=" + support::cpp11::to_string(input1->info()->dimension(0))) };
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_mm_interleaved_transposed_u8", build_opts));
unsigned int idx = 3 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
_kernel.setArg<int32_t>(idx++, a_offset);
_kernel.setArg<int32_t>(idx++, b_offset);
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
index 39526a2..684e323 100644
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
@@ -48,13 +48,13 @@
{
}
-void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, float alpha)
+void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, float alpha, bool is_interleaved_transposed)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1, output);
ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1, output);
- if(output->info()->dimension(1) == 1)
+ if(!is_interleaved_transposed)
{
ARM_COMPUTE_ERROR_ON(input0->info()->dimension(0) != input1->info()->dimension(1));
}
@@ -72,64 +72,36 @@
_lws_hint = cl::NDRange(8, 8);
}
- std::ostringstream mm_arguments;
- mm_arguments << "-DWIDTH_MATRIX_B=" << input1->info()->dimension(0) << " ";
+ std::set<std::string> build_opts;
+ build_opts.emplace(("-DCOLS_A=" + support::cpp11::to_string(input0->info()->dimension(0))));
+ build_opts.emplace(("-DCOLS_B=" + support::cpp11::to_string(input1->info()->dimension(0))));
+
if(is_data_type_fixed_point(input0->info()->data_type()))
{
- mm_arguments << "-DALPHA=" << (input0->info()->data_type() == DataType::QS8 ?
- sqcvt_qs8_f32(alpha, input0->info()->fixed_point_position()) :
- sqcvt_qs16_f32(alpha, input0->info()->fixed_point_position()))
- << " ";
- mm_arguments << "-DFIXED_POINT_POSITION=" << input0->info()->fixed_point_position() << " ";
+ build_opts.emplace(("-DALPHA=" + support::cpp11::to_string((input0->info()->data_type() == DataType::QS8 ?
+ sqcvt_qs8_f32(alpha, input0->info()->fixed_point_position()) :
+ sqcvt_qs16_f32(alpha, input0->info()->fixed_point_position())))));
+
+ build_opts.emplace(("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input0->info()->fixed_point_position())));
}
else
{
- mm_arguments << "-DALPHA=" << alpha << " ";
+ build_opts.emplace(("-DALPHA=" + float_to_string_with_full_precision(alpha)));
}
- std::set<std::string> build_opts;
- // Check if the output tensor is a vector. If so,the kernel runs the vector-matrix multiplication
- if(output->info()->dimension(1) == 1)
+ if(is_interleaved_transposed)
{
- mm_arguments << "-DWIDTH_VECTOR_A=" << input0->info()->dimension(0) << " ";
- build_opts.emplace(mm_arguments.str());
-
- // Create kernel
- std::string data_type_name = lower_string(string_from_data_type(input0->info()->data_type()));
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(("gemm_vm_" + data_type_name), build_opts));
-
- // Configure window kernel
- const unsigned int num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(input0->info()->data_type());
-
- Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration_x));
-
- AccessWindowStatic input0_access(input0->info(), 0, 0, input0->info()->tensor_shape().x(), 1);
- AccessWindowHorizontal input1_access(input1->info(), 0, num_elems_processed_per_iteration_x);
- AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration_x);
-
- update_window_and_padding(win, input0_access, input1_access, output_access);
-
- Coordinates coord;
- coord.set_num_dimensions(output->info()->num_dimensions());
- output_access.set_valid_region(win, ValidRegion(coord, output->info()->tensor_shape()));
-
- ICLKernel::configure(win);
- }
- else
- {
- build_opts.emplace(mm_arguments.str());
-
// Create kernel
std::string data_type_name = lower_string(string_from_data_type(input0->info()->data_type()));
if(data_type_name == "f32")
{
GPUTarget arch_target = get_arch_from_target(get_target());
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_mm_f32_" + string_from_target(arch_target), build_opts));
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_mm_interleaved_transposed_f32_" + string_from_target(arch_target), build_opts));
}
else
{
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_mm_" + data_type_name, build_opts));
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_mm_interleaved_transposed_" + data_type_name, build_opts));
}
// Configure window kernel
@@ -148,6 +120,44 @@
ICLKernel::configure(win);
}
+ else // The input tensors have not been reshaped
+ {
+ ARM_COMPUTE_ERROR_ON(input0->info()->dimension(0) != input1->info()->dimension(1));
+
+ // Special case for 1xN, 2xN, 3xN and 4xN input0 tensor
+ const unsigned int num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(input0->info()->data_type());
+ const unsigned int num_elems_processed_per_iteration_y = std::min(static_cast<int>(output->info()->dimension(1)), 4);
+
+ build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input0->info()->data_type())));
+ build_opts.emplace(("-DNUM_ELEMS_PROCESSED_PER_THREAD_X=" + support::cpp11::to_string(num_elems_processed_per_iteration_x)));
+ build_opts.emplace(("-DNUM_ELEMS_PROCESSED_PER_THREAD_Y=" + support::cpp11::to_string(num_elems_processed_per_iteration_y)));
+
+ // Create kernel
+ if(is_data_type_fixed_point(input0->info()->data_type()))
+ {
+ std::string kernel_name = "gemm_mm_" + lower_string(string_from_data_type(input0->info()->data_type()));
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel((kernel_name), build_opts));
+ }
+ else
+ {
+ std::string kernel_name = "gemm_mm_floating_point";
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel((kernel_name), build_opts));
+ }
+
+ Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
+
+ AccessWindowStatic input0_access(input0->info(), 0, 0, input0->info()->dimension(0), ceil_to_multiple(input0->info()->dimension(1), num_elems_processed_per_iteration_y));
+ AccessWindowStatic input1_access(input1->info(), 0, 0, ceil_to_multiple(input1->info()->dimension(0), num_elems_processed_per_iteration_x), input1->info()->dimension(1));
+ AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
+
+ update_window_and_padding(win, input0_access, input1_access, output_access);
+
+ Coordinates coord;
+ coord.set_num_dimensions(output->info()->num_dimensions());
+ output_access.set_valid_region(win, ValidRegion(coord, output->info()->tensor_shape()));
+
+ ICLKernel::configure(win);
+ }
}
void CLGEMMMatrixMultiplyKernel::run(const Window &window, cl::CommandQueue &queue)
@@ -157,9 +167,9 @@
Window slice = window.first_slice_window_2D();
Window slice_matrix_b = slice;
- slice_matrix_b.set(Window::DimX, Window::Dimension(0, _input1->info()->dimension(0), 1));
- slice_matrix_b.set(Window::DimY, Window::Dimension(0, _input1->info()->dimension(1), 1));
- slice_matrix_b.set(Window::DimZ, Window::Dimension(0, 1, 1));
+
+ slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1));
+ slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1));
do
{