CpuMul changes to enable fp16 in armv8a multi_isa builds

* Moved fp16 and fp32 to their corresponding files
  src/cpu/kernels/mul/generic/neon/fp16.cpp and
  src/cpu/kernels/mul/generic/neon/fp32.cpp

* Changes in filelist.json: added a new fp16.cpp file for the float16_t kernels

* Partially resolves MLCE-1102

Change-Id: I88f24cf034c11b55ff84644b182ba76c7cb94296
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10778
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>

1 files changed, 138 insertions, 0 deletions

diff --git a/src/cpu/kernels/mul/generic/neon/fp32.cpp b/src/cpu/kernels/mul/generic/neon/fp32.cpp
new file mode 100644
index 0000000000..3001eb5110
--- /dev/null
+++ b/src/cpu/kernels/mul/generic/neon/fp32.cpp
@@ -0,0 +1,138 @@
+/*
+ * Copyright (c) 2023 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/ITensor.h"
+#include "arm_compute/core/TensorInfo.h"
+
+#include "src/core/CPP/Validate.h"
+#include "src/core/NEON/wrapper/wrapper.h"
+#include "src/cpu/CpuTypes.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+void mul_F32_F32_F32(const ITensor *src1, const ITensor *src2, ITensor *out, const Window &window, float scale)
+{
+    // Create input windows
+    Window input1_win = window.broadcast_if_dimension_le_one(src1->info()->tensor_shape());
+    Window input2_win = window.broadcast_if_dimension_le_one(src2->info()->tensor_shape());
+
+    // Clear X Dimension on execution window as we handle manually
+    Window win = window;
+    win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+    constexpr int window_step_x         = 16 / sizeof(float);
+    const auto    window_start_x        = static_cast<int>(window.x().start());
+    const auto    window_end_x          = static_cast<int>(window.x().end());
+    const bool    is_broadcast_across_x = src1->info()->tensor_shape().x() != src2->info()->tensor_shape().x();
+
+    using ExactTagType = typename wrapper::traits::neon_vector<float, window_step_x>::tag_type;
+
+    if (is_broadcast_across_x)
+    {
+        const bool     is_broadcast_input_2 = input2_win.x().step() == 0;
+        Window         broadcast_win        = is_broadcast_input_2 ? input2_win : input1_win;
+        Window         non_broadcast_win    = !is_broadcast_input_2 ? input2_win : input1_win;
+        const ITensor *broadcast_tensor     = is_broadcast_input_2 ? src2 : src1;
+        const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? src2 : src1;
+
+        // Clear X Dimension on execution window as we handle manually
+        non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+        Iterator broadcast_input(broadcast_tensor, broadcast_win);
+        Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win);
+        Iterator dst(out, win);
+
+        execute_window_loop(
+            win,
+            [&](const Coordinates &)
+            {
+                const auto non_broadcast_input_ptr = reinterpret_cast<const float *>(non_broadcast_input.ptr());
+                const auto output_ptr              = reinterpret_cast<float *>(dst.ptr());
+
+                const float broadcast_value     = *reinterpret_cast<const float *>(broadcast_input.ptr());
+                const auto  broadcast_value_vec = wrapper::vdup_n(broadcast_value, ExactTagType{});
+                const auto  scale_vec           = wrapper::vdup_n(scale, ExactTagType{});
+
+                // Compute window_step_x elements per iteration
+                int x = window_start_x;
+                for (; x <= (window_end_x - window_step_x); x += window_step_x)
+                {
+                    const auto non_broadcast_v = wrapper::vloadq(non_broadcast_input_ptr + x);
+                    auto       res = wrapper::vmul(wrapper::vmul(broadcast_value_vec, non_broadcast_v), scale_vec);
+                    wrapper::vstore(output_ptr + x, res);
+                }
+
+                // Compute left-over elements
+                for (; x < window_end_x; ++x)
+                {
+                    const auto non_broadcast_v = *(non_broadcast_input_ptr + x);
+                    *(output_ptr + x)          = broadcast_value * non_broadcast_v * scale;
+                }
+            },
+            broadcast_input, non_broadcast_input, dst);
+    }
+    else
+    {
+        // Clear X Dimension on execution window as we handle manually
+        input1_win.set(Window::DimX, Window::Dimension(0, 1, 1));
+        input2_win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+        Iterator input1(src1, input1_win);
+        Iterator input2(src2, input2_win);
+        Iterator dst(out, win);
+
+        execute_window_loop(
+            win,
+            [&](const Coordinates &)
+            {
+                const auto input1_ptr = reinterpret_cast<const float *>(input1.ptr());
+                const auto input2_ptr = reinterpret_cast<const float *>(input2.ptr());
+                const auto output_ptr = reinterpret_cast<float *>(dst.ptr());
+
+                // Compute window_step_x elements per iteration
+                int x = window_start_x;
+                for (; x <= (window_end_x - window_step_x); x += window_step_x)
+                {
+                    const auto ta1       = wrapper::vloadq(input1_ptr + x);
+                    const auto ta2       = wrapper::vloadq(input2_ptr + x);
+                    const auto scale_vec = wrapper::vdup_n(scale, ExactTagType{});
+                    const auto res       = wrapper::vmul(wrapper::vmul(ta1, ta2), scale_vec);
+                    wrapper::vstore(output_ptr + x, res);
+                }
+
+                // Compute left-over elements
+                for (; x < window_end_x; ++x)
+                {
+                    const auto ta1    = *(input1_ptr + x);
+                    const auto ta2    = *(input2_ptr + x);
+                    *(output_ptr + x) = ta1 * ta2 * scale;
+                }
+            },
+            input1, input2, dst);
+    }
+}
+} // namespace cpu
+} // namespace arm_compute