COMPMID-970 : Remove QS8 / QS16 support
Removed fixed point related code.
Change-Id: I487acf138dace3b0450e0d72ca7071eaec254566
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/137678
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/src/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.cpp b/src/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.cpp
index 69b052a..196398a 100644
--- a/src/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.cpp
+++ b/src/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.cpp
@@ -356,263 +356,6 @@
}
template <bool multiply_alpha>
-void vector_matrix_multiply_qs8(const ITensor *input0, const ITensor *input1, ITensor *output, const Window &window, const ThreadInfo &info, float alpha)
-{
- const auto width_matrix_b = static_cast<int>(output->info()->dimension(0));
- const auto in_b_stride = static_cast<int>(input1->info()->strides_in_bytes()[1] / data_size_from_type(input1->info()->data_type()));
- const auto num_elems_vec_a = static_cast<int>(input0->info()->dimension(0));
- const int fixed_point_position = input0->info()->fixed_point_position();
-
- // The implementation computes 32 elements per iteration
- const int window_start_x = 32 * info.thread_id;
- const int window_step_x = 32 * info.num_threads;
- // Make sure (window_end_x - window_start_x) is a multiple of window_step_x
- const int window_end_x = ceil_to_multiple(width_matrix_b - window_start_x, window_step_x) + window_start_x;
-
- Window win_out(window);
- win_out.set(Window::DimX, Window::Dimension(window_start_x, window_end_x, window_step_x));
- win_out.set(Window::DimY, Window::Dimension(0, 1, 1));
-
- Window win_a(window);
- win_a.set(Window::DimX, Window::Dimension(0, 0, 0));
- win_a.set(Window::DimY, Window::Dimension(0, 0, 0));
-
- Window win_b;
- // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
- // This scenario can happen when the the matrix multiplication is used to perform a convolution operation
- if(input1->info()->num_dimensions() >= 3)
- {
- win_b = window;
- }
- win_b.set(Window::DimX, Window::Dimension(window_start_x, window_end_x, window_step_x));
- win_b.set(Window::DimY, Window::Dimension(0, 1, 1));
-
- Iterator ina(input0, win_a);
- Iterator inb(input1, win_b);
- Iterator out(output, win_out);
-
- execute_window_loop(win_out, [&](const Coordinates & id)
- {
- if(id.x() > width_matrix_b)
- {
- return;
- }
-
- // Reset accumulators
- qint16x8_t acc00_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc01_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc02_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc03_qs16 = vdupq_n_qs16(0);
-
- auto vec_a = reinterpret_cast<const qint8_t *>(ina.ptr());
- auto matrix_b = reinterpret_cast<const qint8_t *>(inb.ptr());
-
- auto vec_a_end_addr = vec_a + num_elems_vec_a;
- for(; vec_a <= (vec_a_end_addr - 2);)
- {
- const qint8x8_t a0 = vld1_dup_qs8(vec_a + 0);
- const qint8x8_t a1 = vld1_dup_qs8(vec_a + 1);
-
- const qint8x8_t b00 = vld1_qs8(matrix_b + 0 + 0 * in_b_stride);
- const qint8x8_t b01 = vld1_qs8(matrix_b + 8 + 0 * in_b_stride);
- const qint8x8_t b02 = vld1_qs8(matrix_b + 16 + 0 * in_b_stride);
- const qint8x8_t b03 = vld1_qs8(matrix_b + 24 + 0 * in_b_stride);
- const qint8x8_t b10 = vld1_qs8(matrix_b + 0 + 1 * in_b_stride);
- const qint8x8_t b11 = vld1_qs8(matrix_b + 8 + 1 * in_b_stride);
- const qint8x8_t b12 = vld1_qs8(matrix_b + 16 + 1 * in_b_stride);
- const qint8x8_t b13 = vld1_qs8(matrix_b + 24 + 1 * in_b_stride);
-
- // First accumulation
- acc00_qs16 = vqmlal_qs8(acc00_qs16, b00, a0, fixed_point_position);
- acc01_qs16 = vqmlal_qs8(acc01_qs16, b01, a0, fixed_point_position);
- acc02_qs16 = vqmlal_qs8(acc02_qs16, b02, a0, fixed_point_position);
- acc03_qs16 = vqmlal_qs8(acc03_qs16, b03, a0, fixed_point_position);
-
- // Second accumulation
- acc00_qs16 = vqmlal_qs8(acc00_qs16, b10, a1, fixed_point_position);
- acc01_qs16 = vqmlal_qs8(acc01_qs16, b11, a1, fixed_point_position);
- acc02_qs16 = vqmlal_qs8(acc02_qs16, b12, a1, fixed_point_position);
- acc03_qs16 = vqmlal_qs8(acc03_qs16, b13, a1, fixed_point_position);
-
- vec_a += 2;
- matrix_b += 2 * in_b_stride;
- }
-
- for(; vec_a < vec_a_end_addr;)
- {
- const qint8x8_t a0 = vld1_dup_qs8(vec_a);
-
- const qint8x8_t b00 = vld1_qs8(matrix_b + 0);
- const qint8x8_t b01 = vld1_qs8(matrix_b + 8);
- const qint8x8_t b02 = vld1_qs8(matrix_b + 16);
- const qint8x8_t b03 = vld1_qs8(matrix_b + 24);
-
- acc00_qs16 = vqmlal_qs8(acc00_qs16, b00, a0, fixed_point_position);
- acc01_qs16 = vqmlal_qs8(acc01_qs16, b01, a0, fixed_point_position);
- acc02_qs16 = vqmlal_qs8(acc02_qs16, b02, a0, fixed_point_position);
- acc03_qs16 = vqmlal_qs8(acc03_qs16, b03, a0, fixed_point_position);
-
- vec_a += 1;
- matrix_b += in_b_stride;
- }
-
- // Convert back to qint8x8_t and saturate
- qint8x8_t acc00_qs8 = vqmovn_qs16(acc00_qs16);
- qint8x8_t acc01_qs8 = vqmovn_qs16(acc01_qs16);
- qint8x8_t acc02_qs8 = vqmovn_qs16(acc02_qs16);
- qint8x8_t acc03_qs8 = vqmovn_qs16(acc03_qs16);
-
- // Multiply by the weight of the matrix product (alpha)
- if(multiply_alpha)
- {
- const qint8x8_t alpha_qs8 = vdup_n_qs8(sqcvt_qs8_f32(alpha, fixed_point_position));
- acc00_qs8 = vqmul_qs8(acc00_qs8, alpha_qs8, fixed_point_position);
- acc01_qs8 = vqmul_qs8(acc01_qs8, alpha_qs8, fixed_point_position);
- acc02_qs8 = vqmul_qs8(acc02_qs8, alpha_qs8, fixed_point_position);
- acc03_qs8 = vqmul_qs8(acc03_qs8, alpha_qs8, fixed_point_position);
- }
-
- const auto mtx_out0 = reinterpret_cast<qint8_t *>(out.ptr());
-
- // Store 8x4 output elements
- vst1_qs8(mtx_out0 + 0, acc00_qs8);
- vst1_qs8(mtx_out0 + 8, acc01_qs8);
- vst1_qs8(mtx_out0 + 16, acc02_qs8);
- vst1_qs8(mtx_out0 + 24, acc03_qs8);
- },
- ina, inb, out);
-}
-
-template <bool multiply_alpha>
-void vector_matrix_multiply_qs16(const ITensor *input0, const ITensor *input1, ITensor *output, const Window &window, const ThreadInfo &info, float alpha)
-{
- const auto width_matrix_b = static_cast<int>(output->info()->dimension(0));
- const auto in_b_stride = static_cast<int>(input1->info()->strides_in_bytes()[1] / data_size_from_type(input1->info()->data_type()));
- const auto num_elems_vec_a = static_cast<int>(input0->info()->dimension(0));
- const int fixed_point_position = input0->info()->fixed_point_position();
-
- // The implementation computes 16 elements per iteration
- const int window_start_x = 16 * info.thread_id;
- const int window_step_x = 16 * info.num_threads;
- // Make sure (window_end_x - window_start_x) is a multiple of window_step_x
- const int window_end_x = ceil_to_multiple(width_matrix_b - window_start_x, window_step_x) + window_start_x;
- ARM_COMPUTE_ERROR_ON_MSG((window_end_x - window_start_x) % window_step_x, " (window_end_x - window_start_x) must be multiple of window_step_x");
-
- Window win_out(window);
- win_out.set(Window::DimX, Window::Dimension(window_start_x, window_end_x, window_step_x));
- win_out.set(Window::DimY, Window::Dimension(0, 1, 1));
-
- Window win_a(window);
- win_a.set(Window::DimX, Window::Dimension(0, 0, 0));
- win_a.set(Window::DimY, Window::Dimension(0, 0, 0));
-
- Window win_b;
- // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
- // This scenario can happen when the the matrix multiplication is used to perform a convolution operation
- if(input1->info()->num_dimensions() >= 3)
- {
- win_b = window;
- }
- win_b.set(Window::DimX, Window::Dimension(window_start_x, window_end_x, window_step_x));
- win_b.set(Window::DimY, Window::Dimension(0, 1, 1));
-
- Iterator ina(input0, win_a);
- Iterator inb(input1, win_b);
- Iterator out(output, win_out);
-
- execute_window_loop(win_out, [&](const Coordinates & id)
- {
- if(id.x() > width_matrix_b)
- {
- return;
- }
-
- // Reset accumulators
- qint32x4_t acc00_qs32 = vdupq_n_qs32(0);
- qint32x4_t acc01_qs32 = vdupq_n_qs32(0);
- qint32x4_t acc02_qs32 = vdupq_n_qs32(0);
- qint32x4_t acc03_qs32 = vdupq_n_qs32(0);
-
- auto vec_a = reinterpret_cast<const qint16_t *>(ina.ptr());
- auto matrix_b = reinterpret_cast<const qint16_t *>(inb.ptr());
-
- auto vec_a_end_addr = vec_a + num_elems_vec_a;
- for(; vec_a <= (vec_a_end_addr - 2);)
- {
- const qint16x4_t a0 = vld1_dup_qs16(vec_a + 0);
- const qint16x4_t a1 = vld1_dup_qs16(vec_a + 1);
-
- const qint16x4_t b00 = vld1_qs16(matrix_b + 0 + 0 * in_b_stride);
- const qint16x4_t b01 = vld1_qs16(matrix_b + 4 + 0 * in_b_stride);
- const qint16x4_t b02 = vld1_qs16(matrix_b + 8 + 0 * in_b_stride);
- const qint16x4_t b03 = vld1_qs16(matrix_b + 12 + 0 * in_b_stride);
- const qint16x4_t b10 = vld1_qs16(matrix_b + 0 + 1 * in_b_stride);
- const qint16x4_t b11 = vld1_qs16(matrix_b + 4 + 1 * in_b_stride);
- const qint16x4_t b12 = vld1_qs16(matrix_b + 8 + 1 * in_b_stride);
- const qint16x4_t b13 = vld1_qs16(matrix_b + 12 + 1 * in_b_stride);
-
- // First accumulation
- acc00_qs32 = vqmlal_qs16(acc00_qs32, b00, a0, fixed_point_position);
- acc01_qs32 = vqmlal_qs16(acc01_qs32, b01, a0, fixed_point_position);
- acc02_qs32 = vqmlal_qs16(acc02_qs32, b02, a0, fixed_point_position);
- acc03_qs32 = vqmlal_qs16(acc03_qs32, b03, a0, fixed_point_position);
-
- // Second accumulation
- acc00_qs32 = vqmlal_qs16(acc00_qs32, b10, a1, fixed_point_position);
- acc01_qs32 = vqmlal_qs16(acc01_qs32, b11, a1, fixed_point_position);
- acc02_qs32 = vqmlal_qs16(acc02_qs32, b12, a1, fixed_point_position);
- acc03_qs32 = vqmlal_qs16(acc03_qs32, b13, a1, fixed_point_position);
-
- vec_a += 2;
- matrix_b += 2 * in_b_stride;
- }
-
- for(; vec_a < vec_a_end_addr;)
- {
- const qint16x4_t a0 = vld1_dup_qs16(vec_a);
-
- const qint16x4_t b00 = vld1_qs16(matrix_b + 0);
- const qint16x4_t b01 = vld1_qs16(matrix_b + 4);
- const qint16x4_t b02 = vld1_qs16(matrix_b + 8);
- const qint16x4_t b03 = vld1_qs16(matrix_b + 12);
-
- acc00_qs32 = vqmlal_qs16(acc00_qs32, b00, a0, fixed_point_position);
- acc01_qs32 = vqmlal_qs16(acc01_qs32, b01, a0, fixed_point_position);
- acc02_qs32 = vqmlal_qs16(acc02_qs32, b02, a0, fixed_point_position);
- acc03_qs32 = vqmlal_qs16(acc03_qs32, b03, a0, fixed_point_position);
-
- vec_a += 1;
- matrix_b += in_b_stride;
- }
-
- // Convert back to qint16x4_t and saturate
- qint16x4_t acc00_qs16 = vqmovn_qs32(acc00_qs32);
- qint16x4_t acc01_qs16 = vqmovn_qs32(acc01_qs32);
- qint16x4_t acc02_qs16 = vqmovn_qs32(acc02_qs32);
- qint16x4_t acc03_qs16 = vqmovn_qs32(acc03_qs32);
-
- // Multiply by the weight of the matrix product (alpha)
- if(multiply_alpha)
- {
- const qint16x4_t alpha_qs16 = vdup_n_qs16(sqcvt_qs16_f32(alpha, fixed_point_position));
- acc00_qs16 = vqmul_qs16(acc00_qs16, alpha_qs16, fixed_point_position);
- acc01_qs16 = vqmul_qs16(acc01_qs16, alpha_qs16, fixed_point_position);
- acc02_qs16 = vqmul_qs16(acc02_qs16, alpha_qs16, fixed_point_position);
- acc03_qs16 = vqmul_qs16(acc03_qs16, alpha_qs16, fixed_point_position);
- }
-
- const auto mtx_out0 = reinterpret_cast<qint16_t *>(out.ptr());
-
- // Store 16x4 output elements
- vst1_qs16(mtx_out0 + 0, acc00_qs16);
- vst1_qs16(mtx_out0 + 4, acc01_qs16);
- vst1_qs16(mtx_out0 + 8, acc02_qs16);
- vst1_qs16(mtx_out0 + 12, acc03_qs16);
- },
- ina, inb, out);
-}
-
-template <bool multiply_alpha>
void matrix_matrix_multiply_f32(const ITensor *input0, const ITensor *input1, ITensor *output, const Window &window, float alpha)
{
const size_t in_b_stride = input1->info()->strides_in_bytes()[1] / data_size_from_type(input1->info()->data_type());
@@ -1063,361 +806,12 @@
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
}
-template <bool multiply_alpha>
-void matrix_matrix_multiply_qs8(const ITensor *input0, const ITensor *input1, ITensor *output, const Window &window, float alpha)
-{
- const size_t in_b_stride = input1->info()->strides_in_bytes()[1] / data_size_from_type(input1->info()->data_type());
- const size_t out_stride1 = output->info()->strides_in_bytes()[1] / data_size_from_type(output->info()->data_type());
- const size_t out_stride2 = out_stride1 * 2;
- const size_t out_stride3 = out_stride1 * 3;
- const int num_elems_matrix_b_x = input1->info()->dimension(0);
- const int fixed_point_position = input0->info()->fixed_point_position();
- const qint8x8_t alpha_qs8 = vdup_n_qs8(sqcvt_qs8_f32(alpha, fixed_point_position));
- ARM_COMPUTE_UNUSED(alpha_qs8);
-
- // Set step_x and step_y for matrix A. Scale by a factor of 4 the Y range as the input interleaved matrix A has 4 times less the rows of the output matrix
- Window win_a(window);
- win_a.set(Window::DimX, Window::Dimension(0, 0, 0));
- win_a.set(Window::DimY, Window::Dimension(window.y().start() / 4, std::max(window.y().end() / 4, 1), 1));
-
- Window win_b;
- // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
- // This scenario can happen when the the matrix multiplication is used to perform a convolution operation
- if(input1->info()->num_dimensions() >= 3)
- {
- win_b = window;
- }
- // Set step_x and step_y for matrix B. Scale by a factor of 16 the X range as the input transposed matrix A has 16 times less the cols of the output matrix
- // The step along the x direction is 2 times the in_b_stride because for each iteration we compute 2 blocks of size 16x4
- win_b.set(Window::DimX, Window::Dimension(window.x().start() / 16, window.x().end() / 16, 2 * in_b_stride));
- win_b.set(Window::DimY, Window::Dimension(0, 0, 0));
-
- Iterator ina(input0, win_a);
- Iterator inb(input1, win_b);
- Iterator out(output, window);
-
- // The implementation assumes that the matrix A and Matrix B have been reshaped respectively with NEGEMMInterleave4x4 and NEGEMMTranspose1xW
- // The reshaping of the matrices helps to have a cache friendly implementation and helps to avoid the data re-arrangements needed for computing 16x4 elements per iteration
- // All the values needed for computing a single 32x4 block will be read from consecutive memory positions
- execute_window_loop(window, [&](const Coordinates & id)
- {
- auto mtx_a0 = reinterpret_cast<const qint8_t *>(ina.ptr());
- auto mtx_b0 = reinterpret_cast<const qint8_t *>(inb.ptr());
- auto mtx_b1 = mtx_b0 + in_b_stride;
-
- qint16x8_t acc00_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc10_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc20_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc30_qs16 = vdupq_n_qs16(0);
-
- qint16x8_t acc01_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc11_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc21_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc31_qs16 = vdupq_n_qs16(0);
-
- qint16x8_t acc02_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc12_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc22_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc32_qs16 = vdupq_n_qs16(0);
-
- qint16x8_t acc03_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc13_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc23_qs16 = vdupq_n_qs16(0);
- qint16x8_t acc33_qs16 = vdupq_n_qs16(0);
-
- int k = 0;
- // This for loop performs 2 accumulations
- for(; k <= (num_elems_matrix_b_x - 32); k += 32)
- {
- const qint8x8_t a0 = vld1_dup_qs8(mtx_a0 + 0);
- const qint8x8_t a1 = vld1_dup_qs8(mtx_a0 + 1);
- const qint8x8_t a2 = vld1_dup_qs8(mtx_a0 + 2);
- const qint8x8_t a3 = vld1_dup_qs8(mtx_a0 + 3);
- const qint8x8_t a4 = vld1_dup_qs8(mtx_a0 + 4);
- const qint8x8_t a5 = vld1_dup_qs8(mtx_a0 + 5);
- const qint8x8_t a6 = vld1_dup_qs8(mtx_a0 + 6);
- const qint8x8_t a7 = vld1_dup_qs8(mtx_a0 + 7);
-
- const qint8x8_t b00 = vld1_qs8(mtx_b0 + 0);
- const qint8x8_t b01 = vld1_qs8(mtx_b0 + 8);
- const qint8x8_t b10 = vld1_qs8(mtx_b1 + 0);
- const qint8x8_t b11 = vld1_qs8(mtx_b1 + 8);
-
- // First accumulation
- acc00_qs16 = vqmlal_qs8(acc00_qs16, b00, a0, fixed_point_position);
- acc10_qs16 = vqmlal_qs8(acc10_qs16, b00, a1, fixed_point_position);
- acc20_qs16 = vqmlal_qs8(acc20_qs16, b00, a2, fixed_point_position);
- acc30_qs16 = vqmlal_qs8(acc30_qs16, b00, a3, fixed_point_position);
- acc02_qs16 = vqmlal_qs8(acc02_qs16, b10, a0, fixed_point_position);
- acc12_qs16 = vqmlal_qs8(acc12_qs16, b10, a1, fixed_point_position);
- acc22_qs16 = vqmlal_qs8(acc22_qs16, b10, a2, fixed_point_position);
- acc32_qs16 = vqmlal_qs8(acc32_qs16, b10, a3, fixed_point_position);
-
- const qint8x8_t b02 = vld1_qs8(mtx_b0 + 16);
- const qint8x8_t b03 = vld1_qs8(mtx_b0 + 24);
- const qint8x8_t b12 = vld1_qs8(mtx_b1 + 16);
- const qint8x8_t b13 = vld1_qs8(mtx_b1 + 24);
-
- acc01_qs16 = vqmlal_qs8(acc01_qs16, b01, a0, fixed_point_position);
- acc11_qs16 = vqmlal_qs8(acc11_qs16, b01, a1, fixed_point_position);
- acc21_qs16 = vqmlal_qs8(acc21_qs16, b01, a2, fixed_point_position);
- acc31_qs16 = vqmlal_qs8(acc31_qs16, b01, a3, fixed_point_position);
- acc03_qs16 = vqmlal_qs8(acc03_qs16, b11, a0, fixed_point_position);
- acc13_qs16 = vqmlal_qs8(acc13_qs16, b11, a1, fixed_point_position);
- acc23_qs16 = vqmlal_qs8(acc23_qs16, b11, a2, fixed_point_position);
- acc33_qs16 = vqmlal_qs8(acc33_qs16, b11, a3, fixed_point_position);
-
-#if __arm__
- asm volatile("PLD [%0, #128*2]" ::"r"(reinterpret_cast<const uint8_t *>(mtx_a0)));
- asm volatile("PLD [%0, #128*2]" ::"r"(reinterpret_cast<const uint8_t *>(mtx_b0)));
- asm volatile("PLD [%0, #128*2]" ::"r"(reinterpret_cast<const uint8_t *>(mtx_b1)));
-#endif /* __arm__ */
-
- // Second accumulation
- acc00_qs16 = vqmlal_qs8(acc00_qs16, b02, a4, fixed_point_position);
- acc10_qs16 = vqmlal_qs8(acc10_qs16, b02, a5, fixed_point_position);
- acc20_qs16 = vqmlal_qs8(acc20_qs16, b02, a6, fixed_point_position);
- acc30_qs16 = vqmlal_qs8(acc30_qs16, b02, a7, fixed_point_position);
- acc01_qs16 = vqmlal_qs8(acc01_qs16, b03, a4, fixed_point_position);
- acc11_qs16 = vqmlal_qs8(acc11_qs16, b03, a5, fixed_point_position);
- acc21_qs16 = vqmlal_qs8(acc21_qs16, b03, a6, fixed_point_position);
- acc31_qs16 = vqmlal_qs8(acc31_qs16, b03, a7, fixed_point_position);
- acc02_qs16 = vqmlal_qs8(acc02_qs16, b12, a4, fixed_point_position);
- acc12_qs16 = vqmlal_qs8(acc12_qs16, b12, a5, fixed_point_position);
- acc22_qs16 = vqmlal_qs8(acc22_qs16, b12, a6, fixed_point_position);
- acc32_qs16 = vqmlal_qs8(acc32_qs16, b12, a7, fixed_point_position);
- acc03_qs16 = vqmlal_qs8(acc03_qs16, b13, a4, fixed_point_position);
- acc13_qs16 = vqmlal_qs8(acc13_qs16, b13, a5, fixed_point_position);
- acc23_qs16 = vqmlal_qs8(acc23_qs16, b13, a6, fixed_point_position);
- acc33_qs16 = vqmlal_qs8(acc33_qs16, b13, a7, fixed_point_position);
-
- mtx_a0 += 8;
- mtx_b0 += 32;
- mtx_b1 += 32;
- }
-
- // This for loop performs the left over accumulations
- for(; k < num_elems_matrix_b_x; k += 16)
- {
- const qint8x8_t a0 = vld1_dup_qs8(mtx_a0 + 0);
- const qint8x8_t a1 = vld1_dup_qs8(mtx_a0 + 1);
- const qint8x8_t a2 = vld1_dup_qs8(mtx_a0 + 2);
- const qint8x8_t a3 = vld1_dup_qs8(mtx_a0 + 3);
-
- const qint8x8_t b00 = vld1_qs8(mtx_b0 + 0);
- const qint8x8_t b01 = vld1_qs8(mtx_b0 + 8);
- const qint8x8_t b10 = vld1_qs8(mtx_b1 + 0);
- const qint8x8_t b11 = vld1_qs8(mtx_b1 + 8);
-
- acc00_qs16 = vqmlal_qs8(acc00_qs16, b00, a0, fixed_point_position);
- acc10_qs16 = vqmlal_qs8(acc10_qs16, b00, a1, fixed_point_position);
- acc20_qs16 = vqmlal_qs8(acc20_qs16, b00, a2, fixed_point_position);
- acc30_qs16 = vqmlal_qs8(acc30_qs16, b00, a3, fixed_point_position);
- acc01_qs16 = vqmlal_qs8(acc01_qs16, b01, a0, fixed_point_position);
- acc11_qs16 = vqmlal_qs8(acc11_qs16, b01, a1, fixed_point_position);
- acc21_qs16 = vqmlal_qs8(acc21_qs16, b01, a2, fixed_point_position);
- acc31_qs16 = vqmlal_qs8(acc31_qs16, b01, a3, fixed_point_position);
- acc02_qs16 = vqmlal_qs8(acc02_qs16, b10, a0, fixed_point_position);
- acc12_qs16 = vqmlal_qs8(acc12_qs16, b10, a1, fixed_point_position);
- acc22_qs16 = vqmlal_qs8(acc22_qs16, b10, a2, fixed_point_position);
- acc32_qs16 = vqmlal_qs8(acc32_qs16, b10, a3, fixed_point_position);
- acc03_qs16 = vqmlal_qs8(acc03_qs16, b11, a0, fixed_point_position);
- acc13_qs16 = vqmlal_qs8(acc13_qs16, b11, a1, fixed_point_position);
- acc23_qs16 = vqmlal_qs8(acc23_qs16, b11, a2, fixed_point_position);
- acc33_qs16 = vqmlal_qs8(acc33_qs16, b11, a3, fixed_point_position);
-
- mtx_a0 += 4;
- mtx_b0 += 16;
- mtx_b1 += 16;
- }
-
- // Convert back to qint8x8_t and saturate
- qint8x8_t acc00_qs8 = vqmovn_qs16(acc00_qs16);
- qint8x8_t acc10_qs8 = vqmovn_qs16(acc10_qs16);
- qint8x8_t acc20_qs8 = vqmovn_qs16(acc20_qs16);
- qint8x8_t acc30_qs8 = vqmovn_qs16(acc30_qs16);
-
- qint8x8_t acc01_qs8 = vqmovn_qs16(acc01_qs16);
- qint8x8_t acc11_qs8 = vqmovn_qs16(acc11_qs16);
- qint8x8_t acc21_qs8 = vqmovn_qs16(acc21_qs16);
- qint8x8_t acc31_qs8 = vqmovn_qs16(acc31_qs16);
-
- qint8x8_t acc02_qs8 = vqmovn_qs16(acc02_qs16);
- qint8x8_t acc12_qs8 = vqmovn_qs16(acc12_qs16);
- qint8x8_t acc22_qs8 = vqmovn_qs16(acc22_qs16);
- qint8x8_t acc32_qs8 = vqmovn_qs16(acc32_qs16);
-
- qint8x8_t acc03_qs8 = vqmovn_qs16(acc03_qs16);
- qint8x8_t acc13_qs8 = vqmovn_qs16(acc13_qs16);
- qint8x8_t acc23_qs8 = vqmovn_qs16(acc23_qs16);
- qint8x8_t acc33_qs8 = vqmovn_qs16(acc33_qs16);
-
- // Multiply by the weight of the matrix product (alpha)
- if(multiply_alpha)
- {
- acc00_qs8 = vqmul_qs8(acc00_qs8, alpha_qs8, fixed_point_position);
- acc10_qs8 = vqmul_qs8(acc10_qs8, alpha_qs8, fixed_point_position);
- acc20_qs8 = vqmul_qs8(acc20_qs8, alpha_qs8, fixed_point_position);
- acc30_qs8 = vqmul_qs8(acc30_qs8, alpha_qs8, fixed_point_position);
- acc01_qs8 = vqmul_qs8(acc01_qs8, alpha_qs8, fixed_point_position);
- acc11_qs8 = vqmul_qs8(acc11_qs8, alpha_qs8, fixed_point_position);
- acc21_qs8 = vqmul_qs8(acc21_qs8, alpha_qs8, fixed_point_position);
- acc31_qs8 = vqmul_qs8(acc31_qs8, alpha_qs8, fixed_point_position);
- acc02_qs8 = vqmul_qs8(acc02_qs8, alpha_qs8, fixed_point_position);
- acc12_qs8 = vqmul_qs8(acc12_qs8, alpha_qs8, fixed_point_position);
- acc22_qs8 = vqmul_qs8(acc22_qs8, alpha_qs8, fixed_point_position);
- acc32_qs8 = vqmul_qs8(acc32_qs8, alpha_qs8, fixed_point_position);
- acc03_qs8 = vqmul_qs8(acc03_qs8, alpha_qs8, fixed_point_position);
- acc13_qs8 = vqmul_qs8(acc13_qs8, alpha_qs8, fixed_point_position);
- acc23_qs8 = vqmul_qs8(acc23_qs8, alpha_qs8, fixed_point_position);
- acc33_qs8 = vqmul_qs8(acc33_qs8, alpha_qs8, fixed_point_position);
- }
-
- const auto mtx_out0 = reinterpret_cast<qint8_t *>(out.ptr());
-
- // Store 32x4 output elements
- vst1_qs8(mtx_out0 + 0, acc00_qs8);
- vst1_qs8(mtx_out0 + 8, acc01_qs8);
- vst1_qs8(mtx_out0 + 16, acc02_qs8);
- vst1_qs8(mtx_out0 + 24, acc03_qs8);
- vst1_qs8(mtx_out0 + out_stride1 + 0, acc10_qs8);
- vst1_qs8(mtx_out0 + out_stride1 + 8, acc11_qs8);
- vst1_qs8(mtx_out0 + out_stride1 + 16, acc12_qs8);
- vst1_qs8(mtx_out0 + out_stride1 + 24, acc13_qs8);
- vst1_qs8(mtx_out0 + out_stride2 + 0, acc20_qs8);
- vst1_qs8(mtx_out0 + out_stride2 + 8, acc21_qs8);
- vst1_qs8(mtx_out0 + out_stride2 + 16, acc22_qs8);
- vst1_qs8(mtx_out0 + out_stride2 + 24, acc23_qs8);
- vst1_qs8(mtx_out0 + out_stride3 + 0, acc30_qs8);
- vst1_qs8(mtx_out0 + out_stride3 + 8, acc31_qs8);
- vst1_qs8(mtx_out0 + out_stride3 + 16, acc32_qs8);
- vst1_qs8(mtx_out0 + out_stride3 + 24, acc33_qs8);
- },
- ina, inb, out);
-}
-
-template <bool multiply_alpha>
-void matrix_matrix_multiply_qs16(const ITensor *input0, const ITensor *input1, ITensor *output, const Window &window, float alpha)
-{
- const size_t in_b_stride = input1->info()->strides_in_bytes()[1] / data_size_from_type(input1->info()->data_type());
- const size_t out_stride1 = output->info()->strides_in_bytes()[1] / data_size_from_type(output->info()->data_type());
- const size_t out_stride2 = out_stride1 * 2;
- const size_t out_stride3 = out_stride1 * 3;
- const int num_elems_matrix_b_x = input1->info()->dimension(0);
- const int fixed_point_position = input0->info()->fixed_point_position();
- const qint16x4_t alpha_qs16 = vdup_n_qs16(sqcvt_qs16_f32(alpha, fixed_point_position));
- ARM_COMPUTE_UNUSED(alpha_qs16);
-
- // Set step_x and step_y for matrix A. Scale by a factor of 4 the Y range as the input interleaved matrix A has 4 times less the rows of the output matrix
- Window win_a(window);
- win_a.set(Window::DimX, Window::Dimension(0, 0, 0));
- win_a.set(Window::DimY, Window::Dimension(window.y().start() / 4, std::max(window.y().end() / 4, 1), 1));
-
- Window win_b;
- // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
- // This scenario can happen when the the matrix multiplication is used to perform a convolution operation
- if(input1->info()->num_dimensions() >= 3)
- {
- win_b = window;
- }
- // Set step_x and step_y for matrix B. Scale by a factor of 16 the X range as the input transposed matrix A has 16 times less the cols of the output matrix
- win_b.set(Window::DimX, Window::Dimension(window.x().start() / 8, window.x().end() / 8, in_b_stride));
- win_b.set(Window::DimY, Window::Dimension(0, 0, 0));
-
- Iterator ina(input0, win_a);
- Iterator inb(input1, win_b);
- Iterator out(output, window);
-
- // The implementation assumes that the matrix A and Matrix B have been reshaped respectively with NEGEMMInterleave4x4 and NEGEMMTranspose1xW
- // The reshaping of the matrices helps to have a cache friendly implementation and helps to avoid the data re-arrangements needed for computing 8x4 elements per iteration
- // All the values needed for computing a single 8x4 block will be read from consecutive memory positions
- execute_window_loop(window, [&](const Coordinates & id)
- {
- auto mtx_a0 = reinterpret_cast<const qint16_t *>(ina.ptr());
- auto mtx_b0 = reinterpret_cast<const qint16_t *>(inb.ptr());
- auto mtx_b1 = mtx_b0 + in_b_stride;
-
- qint32x4_t acc00_qs32 = vdupq_n_qs32(0);
- qint32x4_t acc10_qs32 = vdupq_n_qs32(0);
- qint32x4_t acc20_qs32 = vdupq_n_qs32(0);
- qint32x4_t acc30_qs32 = vdupq_n_qs32(0);
-
- qint32x4_t acc01_qs32 = vdupq_n_qs32(0);
- qint32x4_t acc11_qs32 = vdupq_n_qs32(0);
- qint32x4_t acc21_qs32 = vdupq_n_qs32(0);
- qint32x4_t acc31_qs32 = vdupq_n_qs32(0);
-
- // This for loop performs 1 accumulation
- for(int k = 0; k <= (num_elems_matrix_b_x - 8); k += 8)
- {
- const qint16x4_t a0 = vld1_dup_qs16(mtx_a0 + 0);
- const qint16x4_t a1 = vld1_dup_qs16(mtx_a0 + 1);
- const qint16x4_t a2 = vld1_dup_qs16(mtx_a0 + 2);
- const qint16x4_t a3 = vld1_dup_qs16(mtx_a0 + 3);
-
- const qint16x4_t b00 = vld1_qs16(mtx_b0 + 0);
- const qint16x4_t b01 = vld1_qs16(mtx_b0 + 4);
-
- acc00_qs32 = vqmlal_qs16(acc00_qs32, b00, a0, fixed_point_position);
- acc10_qs32 = vqmlal_qs16(acc10_qs32, b00, a1, fixed_point_position);
- acc20_qs32 = vqmlal_qs16(acc20_qs32, b00, a2, fixed_point_position);
- acc30_qs32 = vqmlal_qs16(acc30_qs32, b00, a3, fixed_point_position);
- acc01_qs32 = vqmlal_qs16(acc01_qs32, b01, a0, fixed_point_position);
- acc11_qs32 = vqmlal_qs16(acc11_qs32, b01, a1, fixed_point_position);
- acc21_qs32 = vqmlal_qs16(acc21_qs32, b01, a2, fixed_point_position);
- acc31_qs32 = vqmlal_qs16(acc31_qs32, b01, a3, fixed_point_position);
-
- mtx_a0 += 4;
- mtx_b0 += 8;
- mtx_b1 += 8;
- }
-
- // Convert back to qint16x4_t and saturate
- qint16x4_t acc00_qs16 = vqmovn_qs32(acc00_qs32);
- qint16x4_t acc10_qs16 = vqmovn_qs32(acc10_qs32);
- qint16x4_t acc20_qs16 = vqmovn_qs32(acc20_qs32);
- qint16x4_t acc30_qs16 = vqmovn_qs32(acc30_qs32);
-
- qint16x4_t acc01_qs16 = vqmovn_qs32(acc01_qs32);
- qint16x4_t acc11_qs16 = vqmovn_qs32(acc11_qs32);
- qint16x4_t acc21_qs16 = vqmovn_qs32(acc21_qs32);
- qint16x4_t acc31_qs16 = vqmovn_qs32(acc31_qs32);
-
- // Multiply by the weight of the matrix product (alpha)
- if(multiply_alpha)
- {
- acc00_qs16 = vqmul_qs16(acc00_qs16, alpha_qs16, fixed_point_position);
- acc10_qs16 = vqmul_qs16(acc10_qs16, alpha_qs16, fixed_point_position);
- acc20_qs16 = vqmul_qs16(acc20_qs16, alpha_qs16, fixed_point_position);
- acc30_qs16 = vqmul_qs16(acc30_qs16, alpha_qs16, fixed_point_position);
- acc01_qs16 = vqmul_qs16(acc01_qs16, alpha_qs16, fixed_point_position);
- acc11_qs16 = vqmul_qs16(acc11_qs16, alpha_qs16, fixed_point_position);
- acc21_qs16 = vqmul_qs16(acc21_qs16, alpha_qs16, fixed_point_position);
- acc31_qs16 = vqmul_qs16(acc31_qs16, alpha_qs16, fixed_point_position);
- }
-
- const auto mtx_out0 = reinterpret_cast<qint16_t *>(out.ptr());
-
- // Store 8x4 output elements
- vst1_qs16(mtx_out0 + 0, acc00_qs16);
- vst1_qs16(mtx_out0 + 4, acc01_qs16);
- vst1_qs16(mtx_out0 + out_stride1 + 0, acc10_qs16);
- vst1_qs16(mtx_out0 + out_stride1 + 4, acc11_qs16);
- vst1_qs16(mtx_out0 + out_stride2 + 0, acc20_qs16);
- vst1_qs16(mtx_out0 + out_stride2 + 4, acc21_qs16);
- vst1_qs16(mtx_out0 + out_stride3 + 0, acc30_qs16);
- vst1_qs16(mtx_out0 + out_stride3 + 4, acc31_qs16);
- },
- ina, inb, out);
-}
-
inline Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, float alpha, bool is_interleaved, const GEMMReshapeInfo &reshape_info)
{
ARM_COMPUTE_UNUSED(alpha);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::F16, DataType::F32, DataType::QS8, DataType::QS16);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1, output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1, output);
if(!is_interleaved)
{
@@ -1428,7 +822,6 @@
ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(0) != output->dimension(0));
ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(1) != output->dimension(1));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, output);
}
}
else
@@ -1467,7 +860,6 @@
}
ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(1) != static_cast<size_t>(m));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, output);
}
}
@@ -1492,16 +884,6 @@
num_elems_processed_per_iteration_x = 16;
break;
}
- case DataType::QS8:
- {
- num_elems_processed_per_iteration_x = 32;
- break;
- }
- case DataType::QS16:
- {
- num_elems_processed_per_iteration_x = 16;
- break;
- }
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
{
@@ -1539,16 +921,6 @@
num_elems_processed_per_iteration_x = 8;
break;
}
- case DataType::QS8:
- {
- num_elems_processed_per_iteration_x = 32;
- break;
- }
- case DataType::QS16:
- {
- num_elems_processed_per_iteration_x = 8;
- break;
- }
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
{
@@ -1638,18 +1010,6 @@
vector_matrix_multiply_f32<false>(_input0, _input1, _output, window, info, _alpha);
break;
}
- case DataType::QS8:
- {
- multiply_alpha ? vector_matrix_multiply_qs8<true>(_input0, _input1, _output, window, info, _alpha) :
- vector_matrix_multiply_qs8<false>(_input0, _input1, _output, window, info, _alpha);
- break;
- }
- case DataType::QS16:
- {
- multiply_alpha ? vector_matrix_multiply_qs16<true>(_input0, _input1, _output, window, info, _alpha) :
- vector_matrix_multiply_qs16<false>(_input0, _input1, _output, window, info, _alpha);
- break;
- }
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
{
@@ -1675,18 +1035,6 @@
matrix_matrix_multiply_f32<false>(_input0, _input1, _output, window, _alpha);
break;
}
- case DataType::QS8:
- {
- multiply_alpha ? matrix_matrix_multiply_qs8<true>(_input0, _input1, _output, window, _alpha) :
- matrix_matrix_multiply_qs8<false>(_input0, _input1, _output, window, _alpha);
- break;
- }
- case DataType::QS16:
- {
- multiply_alpha ? matrix_matrix_multiply_qs16<true>(_input0, _input1, _output, window, _alpha) :
- matrix_matrix_multiply_qs16<false>(_input0, _input1, _output, window, _alpha);
- break;
- }
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
{