Port CLGEMM to memory injecting interface

Moves the following kernels:
 - CLGEMMMatrixMultiplyKernel
 - CLGEMMMatrixMultiplyNativeKernel
 - CLGEMMMatrixMultipluReshapedKernel
 - CLGEMMMatrixMultiplyReshapedOnlyRHSKernel

 Moves the following functions
 - CLGEMM

Introduces facilities to easy handling of auxiliary temporary buffers
under then new run interface. Such are:
 - CLAuxTensorHandler: That allows wrapping of workspace buffers memory
 to CLBuffer objects
 - Ability to inject TensorInfo to allocator without transferring
 ownership. This reduce the copy overhead if needed.

Resolves: COMPMID-4188

Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I7055435d831b05b749b26302082e4ac45f26dfb0
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5498
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 12 insertions, 6 deletions

diff --git a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
index 5a9ff7990f..099a2c980f 100644
--- a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
+++ b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
@@ -40,7 +40,7 @@
 #include "src/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h"
 #include "src/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.h"
 #include "src/core/CL/kernels/CLGEMMLowpReductionKernel.h"
-#include "src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h"
+#include "src/core/gpu/cl/kernels/ClGemmReshapeRhsMatrixKernel.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/runtime/CL/gemm_auto_heuristics/CLGEMMAutoHeuristics.h"
 #include "utils/TypePrinter.h"
@@ -127,7 +127,7 @@ inline bool validate_lhs_rhs_info_reshaped_only_rhs(const GEMMLHSMatrixInfo &lhs
     TensorInfo tmp_b_info{};
     // Validate reshape RHS kernel
     auto_init_if_empty(tmp_b_info, b->clone()->set_tensor_shape(compute_rhs_reshaped_shape(*b, rhs_info)));
-    if(!bool(CLGEMMReshapeRHSMatrixKernel::validate(b, &tmp_b_info, rhs_info)))
+    if(!bool(opencl::kernels::ClGemmReshapeRhsMatrixKernel::validate(b, &tmp_b_info, rhs_info)))
     {
         return false;
     }
@@ -192,7 +192,7 @@ CLGEMMLowpMatrixMultiplyCore::CLGEMMLowpMatrixMultiplyCore(std::shared_ptr<IMemo
       _weights_to_qasymm8(std::make_unique<CLDepthConvertLayerKernel>()),
       _mm_native_kernel(std::make_unique<CLGEMMLowpMatrixMultiplyNativeKernel>()),
       _mm_reshaped_only_rhs_kernel(std::make_unique<CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel>()),
-      _mtx_b_reshape_kernel(std::make_unique<CLGEMMReshapeRHSMatrixKernel>()),
+      _mtx_b_reshape_kernel(std::make_unique<opencl::kernels::ClGemmReshapeRhsMatrixKernel>()),
       _mtx_a_reduction_kernel(std::make_unique<CLGEMMLowpMatrixAReductionKernel>()),
       _mtx_b_reduction_kernel(std::make_unique<CLGEMMLowpMatrixBReductionKernel>()),
       _offset_contribution_kernel(std::make_unique<CLGEMMLowpOffsetContributionKernel>()),
@@ -292,7 +292,7 @@ void CLGEMMLowpMatrixMultiplyCore::configure(const CLCompileContext &compile_con
                                                                                  a->info(), _convert_to_qasymm8 ? _qasymm8_weights.info() : b->info(), output->info());
 
         // Configure reshape RHS kernel
-        _mtx_b_reshape_kernel->configure(compile_context, _convert_to_qasymm8 ? &_qasymm8_weights : b, &_tmp_b, rhs_info);
+        _mtx_b_reshape_kernel->configure(compile_context, _convert_to_qasymm8 ? _qasymm8_weights.info() : b->info(), _tmp_b.info(), rhs_info);
     }
 
     // Using default reduction info
@@ -496,7 +496,7 @@ Status CLGEMMLowpMatrixMultiplyCore::validate(const ITensorInfo *a, const ITenso
 
         // Validate reshape RHS kernel
         auto_init_if_empty(tmp_b_info, weights_info.clone()->set_tensor_shape(compute_rhs_reshaped_shape(weights_info, rhs_info)));
-        ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMReshapeRHSMatrixKernel::validate(&weights_info, &tmp_b_info, rhs_info));
+        ARM_COMPUTE_RETURN_ON_ERROR(opencl::kernels::ClGemmReshapeRhsMatrixKernel::validate(&weights_info, &tmp_b_info, rhs_info));
     }
 
     TensorInfo info_vector_sum_col{};
@@ -634,6 +634,9 @@ void CLGEMMLowpMatrixMultiplyCore::run()
         if(!_reshape_b_only_on_first_run)
         {
             // Run reshape matrix B
+            ITensorPack mtx_b_pack;
+            mtx_b_pack.add_const_tensor(TensorType::ACL_SRC, _convert_to_qasymm8 ? &_qasymm8_weights : _original_b);
+            mtx_b_pack.add_tensor(TensorType::ACL_DST, &_tmp_b);
             CLScheduler::get().enqueue(*_mtx_b_reshape_kernel, false);
         }
     }
@@ -687,7 +690,10 @@ void CLGEMMLowpMatrixMultiplyCore::prepare()
 
             // Run reshape kernel and mark original weights tensor as unused
             _tmp_b.allocator()->allocate();
-            CLScheduler::get().enqueue(*_mtx_b_reshape_kernel, false);
+            ITensorPack mtx_b_pack;
+            mtx_b_pack.add_const_tensor(TensorType::ACL_SRC, _convert_to_qasymm8 ? &_qasymm8_weights : _original_b);
+            mtx_b_pack.add_tensor(TensorType::ACL_DST, &_tmp_b);
+            CLScheduler::get().enqueue_op(*_mtx_b_reshape_kernel, mtx_b_pack, false);
             _original_b->mark_as_unused();
         }