COMPMID-3304: Update OpenCL GEMM heuristic for Int8
Change-Id: I6b7ff678d8d0437a1639db2ff602ea1cdb155464
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3056
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
index 90e5698..ef17f11 100644
--- a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
+++ b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
@@ -35,6 +35,7 @@
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
+#include "arm_compute/runtime/CL/gemm/CLGEMMKernelSelection.h"
namespace arm_compute
{
@@ -43,16 +44,33 @@
namespace
{
-inline bool is_gemm_reshaped(bool reshape_b_only_on_first_run, GPUTarget gpu_target)
+inline bool is_gemm_reshaped(unsigned int m, unsigned int n, unsigned int k, DataType data_type, bool reshape_b_only_on_first_run)
{
- return (get_arch_from_target(gpu_target) != GPUTarget::MIDGARD) && (reshape_b_only_on_first_run);
+ std::unique_ptr<ICLGEMMKernelSelection> gemm_kernel = CLGEMMKernelSelectionFactory::create(CLScheduler::get().target());
+ ARM_COMPUTE_ERROR_ON_NULLPTR(gemm_kernel.get());
+
+ CLGEMMKernelSelectionParams params;
+ params.m = m;
+ params.n = n;
+ params.k = k;
+ params.is_rhs_constant = reshape_b_only_on_first_run;
+ params.data_type = data_type;
+
+ switch(gemm_kernel->select_kernel(params))
+ {
+ case CLGEMMKernelType::NATIVE:
+ return false;
+ case CLGEMMKernelType::RESHAPED_ONLY_RHS:
+ return true;
+ default:
+ ARM_COMPUTE_ERROR("Not supported gemmlowp kernel!");
+ }
}
} // namespace
CLGEMMLowpMatrixMultiplyCore::CLGEMMLowpMatrixMultiplyCore(std::shared_ptr<IMemoryManager> memory_manager)
: _memory_group(std::move(memory_manager)),
_weights_to_qasymm8(),
- _mm_midgard_kernel(),
_mm_native_kernel(),
_mm_reshaped_only_rhs_kernel(),
_mtx_b_reshape_kernel(),
@@ -73,7 +91,6 @@
_a_offset(0),
_b_offset(0),
_is_gemm_reshaped(true),
- _is_midgard(false),
_reshape_b_only_on_first_run(false),
_is_prepared(false),
_run_output_stage(false),
@@ -102,7 +119,6 @@
const GPUTarget gpu_target = CLScheduler::get().target();
// Set the target for the kernels
- _mm_midgard_kernel.set_target(gpu_target);
_mm_native_kernel.set_target(gpu_target);
_mm_reshaped_only_rhs_kernel.set_target(gpu_target);
@@ -120,8 +136,7 @@
const int depth_output_gemm3d = gemm_info.depth_output_gemm3d();
// Check if we need to reshape the matrix A and matrix B
- _is_gemm_reshaped = is_gemm_reshaped(_reshape_b_only_on_first_run, gpu_target);
- _is_midgard = gpu_target == GPUTarget::MIDGARD;
+ _is_gemm_reshaped = is_gemm_reshaped(m, n, k, a->info()->data_type(), _reshape_b_only_on_first_run);
if(_convert_to_qasymm8)
{
@@ -220,19 +235,12 @@
}
else
{
- if(_is_midgard)
- {
- // Configure matrix multiply kernel
- _mm_midgard_kernel.configure(_matrix_a, matrix_b, &_mm_result_s32, GEMMReshapeInfo(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d));
- }
- else
- {
- // Pick up the GEMM configuration
- std::tie(lhs_info, rhs_info) = CLGEMMNativeKernelConfigurationFactory::create(gpu_target)->configure(m, n, k, batch_size, DataType::QASYMM8);
+ // Pick up the GEMM configuration
+ std::tie(lhs_info, rhs_info) = CLGEMMNativeKernelConfigurationFactory::create(gpu_target)->configure(m, n, k, batch_size, DataType::QASYMM8);
- // Configure matrix multiply kernel
- _mm_native_kernel.configure(_matrix_a, matrix_b, &_mm_result_s32, lhs_info, rhs_info, GEMMReshapeInfo(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d));
- }
+ // Configure matrix multiply kernel
+ _mm_native_kernel.configure(_matrix_a, matrix_b, &_mm_result_s32, lhs_info, rhs_info, GEMMReshapeInfo(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d));
+
_offset_contribution_output_stage_kernel.configure(&_mm_result_s32, _a_offset == 0 ? nullptr : &_vector_sum_col, _b_offset == 0 ? nullptr : &_vector_sum_row, c, output, a->info()->dimension(0),
_a_offset, _b_offset, gemmlowp_output_stage, &_gemm_output_stage_multipliers, &_gemm_output_stage_shifts);
@@ -260,19 +268,11 @@
}
else
{
- if(_is_midgard)
- {
- // Configure matrix multiply kernel
- _mm_midgard_kernel.configure(_matrix_a, matrix_b, output, GEMMReshapeInfo(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d));
- }
- else
- {
- // Pick up the GEMM configuration
- std::tie(lhs_info, rhs_info) = CLGEMMNativeKernelConfigurationFactory::create(gpu_target)->configure(m, n, k, batch_size, DataType::QASYMM8);
+ // Pick up the GEMM configuration
+ std::tie(lhs_info, rhs_info) = CLGEMMNativeKernelConfigurationFactory::create(gpu_target)->configure(m, n, k, batch_size, DataType::QASYMM8);
- // Configure matrix multiply kernel
- _mm_native_kernel.configure(_matrix_a, matrix_b, output, lhs_info, rhs_info, GEMMReshapeInfo(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d));
- }
+ // Configure matrix multiply kernel
+ _mm_native_kernel.configure(_matrix_a, matrix_b, output, lhs_info, rhs_info, GEMMReshapeInfo(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d));
}
// Configure offset contribution kernel
@@ -329,9 +329,8 @@
const unsigned int k = a->dimension(0);
const unsigned int batch_size = reinterpret_input_as_3d ? a->dimension(3) : a->dimension(2);
const int depth_output_gemm3d = gemm_info.depth_output_gemm3d();
- const bool is_midgard = gpu_target == GPUTarget::MIDGARD;
- bool reshape_matrix_b = is_gemm_reshaped(gemm_info.reshape_b_only_on_first_run(), CLScheduler::get().target());
+ bool reshape_matrix_b = is_gemm_reshaped(m, n, k, a->data_type(), gemm_info.reshape_b_only_on_first_run());
const GEMMReshapeInfo reshape_info = GEMMReshapeInfo(m, n, k, 1, 1, depth_output_gemm3d, reinterpret_input_as_3d);
@@ -425,19 +424,11 @@
// Output tensor auto inizialitation if not yet initialized
auto_init_if_empty(mm_result_s32_info, a->clone()->set_tensor_shape(compute_mm_shape(*matrix_a_info, *matrix_b_info, false, reshape_info)).set_data_type(DataType::S32));
- if(is_midgard)
- {
- // Validate matrix multiply
- ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixMultiplyKernel::validate(matrix_a_info, matrix_b_info, &mm_result_s32_info, reshape_info));
- }
- else
- {
- // Pick up the GEMM configuration
- std::tie(lhs_info, rhs_info) = CLGEMMNativeKernelConfigurationFactory::create(gpu_target)->configure(m, n, k, batch_size, DataType::QASYMM8);
+ // Pick up the GEMM configuration
+ std::tie(lhs_info, rhs_info) = CLGEMMNativeKernelConfigurationFactory::create(gpu_target)->configure(m, n, k, batch_size, DataType::QASYMM8);
- // Validate matrix multiply
- ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixMultiplyNativeKernel::validate(matrix_a_info, matrix_b_info, &mm_result_s32_info, lhs_info, rhs_info, reshape_info));
- }
+ // Validate matrix multiply
+ ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixMultiplyNativeKernel::validate(matrix_a_info, matrix_b_info, &mm_result_s32_info, lhs_info, rhs_info, reshape_info));
}
// Validate offset contribution kernel
@@ -461,19 +452,11 @@
}
else
{
- if(is_midgard)
- {
- // Validate matrix multiply
- ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixMultiplyKernel::validate(matrix_a_info, matrix_b_info, output, reshape_info));
- }
- else
- {
- // Pick up the GEMM configuration
- std::tie(lhs_info, rhs_info) = CLGEMMNativeKernelConfigurationFactory::create(gpu_target)->configure(m, n, k, batch_size, DataType::QASYMM8);
+ // Pick up the GEMM configuration
+ std::tie(lhs_info, rhs_info) = CLGEMMNativeKernelConfigurationFactory::create(gpu_target)->configure(m, n, k, batch_size, DataType::QASYMM8);
- // Validate matrix multiply
- ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixMultiplyNativeKernel::validate(matrix_a_info, matrix_b_info, output, lhs_info, rhs_info, reshape_info));
- }
+ // Validate matrix multiply
+ ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixMultiplyNativeKernel::validate(matrix_a_info, matrix_b_info, output, lhs_info, rhs_info, reshape_info));
}
if(output->total_size() != 0)
@@ -524,14 +507,7 @@
}
else
{
- if(_is_midgard)
- {
- CLScheduler::get().enqueue(_mm_midgard_kernel, false);
- }
- else
- {
- CLScheduler::get().enqueue(_mm_native_kernel, false);
- }
+ CLScheduler::get().enqueue(_mm_native_kernel, false);
}
if(_run_output_stage)
{