COMPMID-344 Updated doxygen

Change-Id: I32f7b84daa560e460b77216add529c8fa8b327ae

1 files changed, 226 insertions, 0 deletions

diff --git a/src/core/NEON/kernels/NELocallyConnectedMatrixMultiplyKernel.cpp b/src/core/NEON/kernels/NELocallyConnectedMatrixMultiplyKernel.cpp
new file mode 100644
index 0000000000..ab84efbf23
--- /dev/null
+++ b/src/core/NEON/kernels/NELocallyConnectedMatrixMultiplyKernel.cpp
@@ -0,0 +1,226 @@
+/*
+ * Copyright (c) 2017 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/core/NEON/kernels/NELocallyConnectedMatrixMultiplyKernel.h"
+
+#include "arm_compute/core/AccessWindowTranspose.h"
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/IAccessWindow.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/NEON/NEFixedPoint.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+
+#include <arm_neon.h>
+#include <cstddef>
+#include <cstdint>
+#include <tuple>
+
+using namespace arm_compute;
+
+namespace arm_compute
+{
+class Coordinates;
+} // namespace arm_compute
+
+namespace
+{
+void vector_matrix_multiply_f32(const ITensor *input0, const ITensor *input1, ITensor *output, const Window &window)
+{
+    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));
+
+    // The implementation computes 16 elements per iteration
+    const int window_start_x = 16 * window.thread_id();
+    const int window_step_x  = 16 * window.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));
+
+    Window win_a(window);
+    win_a.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+    Iterator ina(input0, win_a);
+    Iterator out(output, win_out);
+
+    execute_window_loop(win_out, [&](const Coordinates & id)
+    {
+        if(id.x() > width_matrix_b)
+        {
+            return;
+        }
+
+        float32x4_t acc0 = vdupq_n_f32(0.f);
+        float32x4_t acc1 = vdupq_n_f32(0.f);
+        float32x4_t acc2 = vdupq_n_f32(0.f);
+        float32x4_t acc3 = vdupq_n_f32(0.f);
+
+        auto vec_a    = reinterpret_cast<const float *>(ina.ptr());
+        auto matrix_b = reinterpret_cast<const float *>(input1->ptr_to_element(Coordinates(id[0], 0, id[1])));
+
+#if __arm__
+        asm volatile("PLD [%0, #128*4]" ::"r"(reinterpret_cast<const uint8_t *>(vec_a)));
+        asm volatile("PLD [%0, #128*4]" ::"r"(reinterpret_cast<const uint8_t *>(matrix_b)));
+        asm volatile("PLD [%0, #128*4]" ::"r"(reinterpret_cast<const uint8_t *>(matrix_b + in_b_stride)));
+#endif
+
+        const float *vec_a_end_addr = vec_a + num_elems_vec_a;
+
+        for(; vec_a <= (vec_a_end_addr - 4);)
+        {
+            float32x2_t a0l = vld1_f32(vec_a);
+
+            float32x4_t b00 = vld1q_f32(matrix_b + 0 + 0 * in_b_stride);
+            float32x4_t b01 = vld1q_f32(matrix_b + 4 + 0 * in_b_stride);
+            float32x4_t b02 = vld1q_f32(matrix_b + 8 + 0 * in_b_stride);
+            float32x4_t b03 = vld1q_f32(matrix_b + 12 + 0 * in_b_stride);
+
+            float32x4_t b10 = vld1q_f32(matrix_b + 0 + 1 * in_b_stride);
+            float32x4_t b11 = vld1q_f32(matrix_b + 4 + 1 * in_b_stride);
+            float32x4_t b12 = vld1q_f32(matrix_b + 8 + 1 * in_b_stride);
+            float32x4_t b13 = vld1q_f32(matrix_b + 12 + 1 * in_b_stride);
+
+#if __arm__
+            asm volatile("PLD [%0, #128*4]" ::"r"(reinterpret_cast<const uint8_t *>(vec_a)));
+            asm volatile("PLD [%0, #128*1]" ::"r"(reinterpret_cast<const uint8_t *>(matrix_b + 1 * in_b_stride)));
+            asm volatile("PLD [%0, #128*1]" ::"r"(reinterpret_cast<const uint8_t *>(matrix_b + 2 * in_b_stride)));
+            asm volatile("PLD [%0, #128*1]" ::"r"(reinterpret_cast<const uint8_t *>(matrix_b + 3 * in_b_stride)));
+            asm volatile("PLD [%0, #128*1]" ::"r"(reinterpret_cast<const uint8_t *>(matrix_b + 4 * in_b_stride)));
+#endif
+
+            acc0 = vmlaq_lane_f32(acc0, b00, a0l, 0);
+            acc1 = vmlaq_lane_f32(acc1, b01, a0l, 0);
+            acc2 = vmlaq_lane_f32(acc2, b02, a0l, 0);
+            acc3 = vmlaq_lane_f32(acc3, b03, a0l, 0);
+
+            acc0 = vmlaq_lane_f32(acc0, b10, a0l, 1);
+            acc1 = vmlaq_lane_f32(acc1, b11, a0l, 1);
+            acc2 = vmlaq_lane_f32(acc2, b12, a0l, 1);
+            acc3 = vmlaq_lane_f32(acc3, b13, a0l, 1);
+
+            vec_a += 2;
+            matrix_b += 2 * in_b_stride;
+
+            a0l = vld1_f32(vec_a);
+
+            b00 = vld1q_f32(matrix_b + 0 + 0 * in_b_stride);
+            b01 = vld1q_f32(matrix_b + 4 + 0 * in_b_stride);
+            b02 = vld1q_f32(matrix_b + 8 + 0 * in_b_stride);
+            b03 = vld1q_f32(matrix_b + 12 + 0 * in_b_stride);
+
+            b10 = vld1q_f32(matrix_b + 0 + 1 * in_b_stride);
+            b11 = vld1q_f32(matrix_b + 4 + 1 * in_b_stride);
+            b12 = vld1q_f32(matrix_b + 8 + 1 * in_b_stride);
+            b13 = vld1q_f32(matrix_b + 12 + 1 * in_b_stride);
+
+            acc0 = vmlaq_lane_f32(acc0, b00, a0l, 0);
+            acc1 = vmlaq_lane_f32(acc1, b01, a0l, 0);
+            acc2 = vmlaq_lane_f32(acc2, b02, a0l, 0);
+            acc3 = vmlaq_lane_f32(acc3, b03, a0l, 0);
+
+            acc0 = vmlaq_lane_f32(acc0, b10, a0l, 1);
+            acc1 = vmlaq_lane_f32(acc1, b11, a0l, 1);
+            acc2 = vmlaq_lane_f32(acc2, b12, a0l, 1);
+            acc3 = vmlaq_lane_f32(acc3, b13, a0l, 1);
+
+            vec_a += 2;
+            matrix_b += 2 * in_b_stride;
+        }
+
+        for(; vec_a < vec_a_end_addr;)
+        {
+            const float a0 = *vec_a;
+
+            const float32x4_t b00 = vld1q_f32(matrix_b + 0 + 0 * in_b_stride);
+            const float32x4_t b01 = vld1q_f32(matrix_b + 4 + 0 * in_b_stride);
+            const float32x4_t b02 = vld1q_f32(matrix_b + 8 + 0 * in_b_stride);
+            const float32x4_t b03 = vld1q_f32(matrix_b + 12 + 0 * in_b_stride);
+
+            acc0 = vmlaq_n_f32(acc0, b00, a0);
+            acc1 = vmlaq_n_f32(acc1, b01, a0);
+            acc2 = vmlaq_n_f32(acc2, b02, a0);
+            acc3 = vmlaq_n_f32(acc3, b03, a0);
+
+            vec_a += 1;
+            matrix_b += in_b_stride;
+        }
+
+        const auto vec_out = reinterpret_cast<float *>(out.ptr());
+
+        vst1q_f32(vec_out + 0, acc0);
+        vst1q_f32(vec_out + 4, acc1);
+        vst1q_f32(vec_out + 8, acc2);
+        vst1q_f32(vec_out + 12, acc3);
+    },
+    ina, out);
+}
+} // namespace
+
+NELocallyConnectedMatrixMultiplyKernel::NELocallyConnectedMatrixMultiplyKernel()
+    : _input0(nullptr), _input1(nullptr), _output(nullptr)
+{
+}
+
+void NELocallyConnectedMatrixMultiplyKernel::configure(const ITensor *input0, const ITensor *input1, ITensor *output)
+{
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::F32);
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::F32);
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F32);
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F32);
+    ARM_COMPUTE_ERROR_ON(input0->info()->dimension(0) != input1->info()->dimension(1));
+
+    _input0 = input0;
+    _input1 = input1;
+    _output = output;
+
+    unsigned int num_elems_processed_per_iteration_x = 16;
+
+    // Configure kernel window
+    Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration_x));
+
+    AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration_x);
+
+    update_window_and_padding(win,
+                              AccessWindowHorizontal(input0->info(), 0, num_elems_processed_per_iteration_x),
+                              AccessWindowHorizontal(input1->info(), 0, num_elems_processed_per_iteration_x),
+                              output_access);
+
+    output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->info()->tensor_shape()));
+
+    INEKernel::configure(win);
+}
+
+void NELocallyConnectedMatrixMultiplyKernel::run(const Window &window)
+{
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
+
+    vector_matrix_multiply_f32(_input0, _input1, _output, window);
+}