COMPMID-881: RSH new arm_gemm interface.

Change-Id: I1e2a1a77097d8017c274af3f97eba6964f80f5fa
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/122592
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

1 files changed, 52 insertions, 68 deletions

diff --git a/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp
index ad47593f20..dc4ed5cefb 100644
--- a/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp
+++ b/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp
@@ -26,11 +26,9 @@
 #include "arm_compute/core/Error.h"
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/ITensor.h"
-#include "arm_compute/core/NEON/kernels/NEGEMMAssemblyBaseKernel.h"
 #include "arm_compute/core/NEON/kernels/NEGEMMInterleave4x4Kernel.h"
 #include "arm_compute/core/NEON/kernels/NEGEMMLowpMatrixMultiplyKernel.h"
 #include "arm_compute/core/NEON/kernels/NEGEMMTranspose1xWKernel.h"
-#include "arm_compute/core/NEON/kernels/arm64/NEGEMMLowpAArch64V8P4Kernel.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Types.h"
 #include "arm_compute/core/Validate.h"
@@ -39,18 +37,13 @@
 #include "arm_compute/runtime/TensorAllocator.h"
 #include "support/ToolchainSupport.h"
 
-namespace arm_compute
-{
-#include "arm_compute/core/NEON/kernels/assembly/gemm_interleaved.hpp"
-#include "arm_compute/core/NEON/kernels/assembly/kernels/a64_gemm_u8_12x8.hpp"
-} // namespace arm_compute
-
 using namespace arm_compute;
 using namespace arm_compute::misc::shape_calculator;
 
 NEGEMMLowpMatrixMultiplyCore::NEGEMMLowpMatrixMultiplyCore(std::shared_ptr<IMemoryManager> memory_manager)
-    : _memory_group(std::move(memory_manager)), _mm_kernel(nullptr), _mtx_a_reshape_kernel(nullptr), _mtx_b_reshape_kernel(nullptr), _mtx_a_reduction_kernel(), _mtx_b_reduction_kernel(),
-      _offset_contribution_kernel(), _vector_sum_col(), _vector_sum_row(), _tmp_a(), _tmp_b(), _workspace(), _a_offset(0), _b_offset(0), _run_vector_matrix_multiplication(false), _dot_product_path(false)
+    : _memory_group(std::move(memory_manager)), _asm_glue_unsigned(), _asm_glue_signed(), _mm_kernel(nullptr), _mtx_a_reshape_kernel(nullptr), _mtx_b_reshape_kernel(nullptr), _mtx_a_reduction_kernel(),
+      _mtx_b_reduction_kernel(), _offset_contribution_kernel(), _vector_sum_col(), _vector_sum_row(), _tmp_a(), _tmp_b(), _workspace(), _a_offset(0), _b_offset(0), _run_vector_matrix_multiplication(false),
+      _dot_product_path(false)
 {
 }
 
@@ -64,33 +57,27 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b,
     _b_offset                         = b->info()->quantization_info().offset;
     _run_vector_matrix_multiplication = a->info()->dimension(1) < 2;
 
-#ifdef ARM_COMPUTE_AARCH64_V8_2
-    // Check for DOT product instruction
-    const struct CPUInfo ci              = NEScheduler::get().cpu_info();
-    const int            cpu_has_dotprod = static_cast<int>(ci.CPU) & static_cast<int>(CPUTarget::DOT);
-
-    if(cpu_has_dotprod != 0)
+#ifdef __aarch64__
+    switch(a->info()->data_type())
     {
-        _dot_product_path = true;
-
-        // Configure matrix multiply kernel
-        struct CPUInfo ci = NEScheduler::get().cpu_info();
-        const int      M  = output->info()->tensor_shape().y();
-        const int      N  = output->info()->tensor_shape().x();
-        const int      K  = a->info()->tensor_shape().x();
-
-        const size_t     workbench_size = GemmInterleaved<gemm_u8_12x8, gemm_u8_12x8::operand_type, gemm_u8_12x8::result_type>(&ci, M, N, K, false, false).get_working_size();
-        constexpr size_t alignment      = 4096;
-        _workspace.allocator()->init(TensorInfo(TensorShape{ (workbench_size + alignment - 1) * NEScheduler::get().num_threads() }, 1, DataType::U8));
-        _memory_group.manage(&_workspace);
-
-        // Configure matrix multiplication kernel
-        auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpAArch64V8P4Kernel>();
-        k->configure(a, b, output, &_workspace, 1.f, 1.f, false, false);
-        _mm_kernel = std::move(k);
+        case DataType::S8:
+        {
+            _dot_product_path = setup_assembly_kernel(a, b, nullptr, output, 1.f, 1.f, _workspace, _memory_group, _asm_glue_signed);
+            break;
+        }
+        case DataType::U8:
+        {
+            _dot_product_path = setup_assembly_kernel(a, b, nullptr, output, 1.f, 1.f, _workspace, _memory_group, _asm_glue_unsigned);
+            break;
+        }
+        default:
+        {
+            ARM_COMPUTE_ERROR("Datatype not supported");
+            break;
+        }
     }
-    else
-#endif /* ARM_COMPUTE_AARCH64_V8_2 */
+#endif /* __aarch64__ */
+    if(!_dot_product_path)
     {
         if(_run_vector_matrix_multiplication)
         {
@@ -203,42 +190,28 @@ Status NEGEMMLowpMatrixMultiplyCore::validate(const ITensorInfo *a, const ITenso
     int32_t b_offset                         = b->quantization_info().offset;
     bool    run_vector_matrix_multiplication = a->dimension(1) < 2;
 
-#ifdef ARM_COMPUTE_AARCH64_V8_2
-    // Check for DOT product instruction
-    const struct CPUInfo ci              = NEScheduler::get().cpu_info();
-    const int            cpu_has_dotprod = static_cast<int>(ci.CPU) & static_cast<int>(CPUTarget::DOT);
-
-    if(cpu_has_dotprod != 0)
+    if(!run_vector_matrix_multiplication)
     {
-        // Validate matrix multiply kernel
-        ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMLowpAArch64V8P4Kernel::validate(a, b, output));
+        // The interleaved output matrix will have the following shape: [ a_height * 4, ceil(a_width / 4.0f) ]
+        TensorShape shape_tmp_a = a->tensor_shape();
+        shape_tmp_a.set(0, a->dimension(0) * 4);
+        shape_tmp_a.set(1, std::ceil(a->dimension(1) / 4.f));
+
+        // The transpose1xW output matrix will have the following shape: [ b_height * 16, ceil(b_width / 16.0f) ]
+        TensorShape shape_tmp_b = b->tensor_shape();
+        shape_tmp_b.set(0, b->dimension(1) * 16);
+        shape_tmp_b.set(1, std::ceil(b->dimension(0) / 16.f));
+
+        TensorInfo info_a(shape_tmp_a, 1, a->data_type());
+        TensorInfo info_b(shape_tmp_b, 1, b->data_type());
+
+        ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMInterleave4x4Kernel::validate(a, &info_a));
+        ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMTranspose1xWKernel::validate(b, &info_b));
+        ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMLowpMatrixMultiplyKernel::validate(&info_a, &info_b, output));
     }
     else
-#endif /* ARM_COMPUTE_AARCH64_V8_2 */
     {
-        if(!run_vector_matrix_multiplication)
-        {
-            // The interleaved output matrix will have the following shape: [ a_height * 4, ceil(a_width / 4.0f) ]
-            TensorShape shape_tmp_a = a->tensor_shape();
-            shape_tmp_a.set(0, a->dimension(0) * 4);
-            shape_tmp_a.set(1, std::ceil(a->dimension(1) / 4.f));
-
-            // The transpose1xW output matrix will have the following shape: [ b_height * 16, ceil(b_width / 16.0f) ]
-            TensorShape shape_tmp_b = b->tensor_shape();
-            shape_tmp_b.set(0, b->dimension(1) * 16);
-            shape_tmp_b.set(1, std::ceil(b->dimension(0) / 16.f));
-
-            TensorInfo info_a(shape_tmp_a, 1, a->data_type());
-            TensorInfo info_b(shape_tmp_b, 1, b->data_type());
-
-            ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMInterleave4x4Kernel::validate(a, &info_a));
-            ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMTranspose1xWKernel::validate(b, &info_b));
-            ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMLowpMatrixMultiplyKernel::validate(&info_a, &info_b, output));
-        }
-        else
-        {
-            ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMLowpMatrixMultiplyKernel::validate(a, b, output));
-        }
+        ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMLowpMatrixMultiplyKernel::validate(a, b, output));
     }
 
     TensorInfo info_vector_sum_col, info_vector_sum_row;
@@ -288,7 +261,18 @@ void NEGEMMLowpMatrixMultiplyCore::run()
         }
     }
 
-    NEScheduler::get().schedule(_mm_kernel.get(), Window::DimY);
+    if(_asm_glue_unsigned._optimised_kernel != nullptr)
+    {
+        _asm_glue_unsigned.run();
+    }
+    else if(_asm_glue_signed._optimised_kernel != nullptr)
+    {
+        _asm_glue_signed.run();
+    }
+    else
+    {
+        NEScheduler::get().schedule(_mm_kernel.get(), Window::DimY);
+    }
 
     // Run matrix A reduction kernel only if _b_offset is not equal to 0
     if(_b_offset != 0)