Add TRIAD_PARTED_FUSED kernel

LLNL · Oct 25, 2023 · 1536b7a · 1536b7a
1 parent 580ecb0
commit 1536b7a
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Showing 11 changed files with 1,139 additions and 0 deletions.
diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt
@@ -228,6 +228,9 @@ blt_add_executable(
   stream/TRIAD_PARTED.cpp
   stream/TRIAD_PARTED-Seq.cpp
   stream/TRIAD_PARTED-OMPTarget.cpp
+  stream/TRIAD_PARTED_FUSED.cpp
+  stream/TRIAD_PARTED_FUSED-Seq.cpp
+  stream/TRIAD_PARTED_FUSED-OMPTarget.cpp
   common/DataUtils.cpp
   common/Executor.cpp
   common/KernelBase.cpp

diff --git a/src/common/RAJAPerfSuite.cpp b/src/common/RAJAPerfSuite.cpp
@@ -76,6 +76,7 @@
 #include "stream/ADD.hpp"
 #include "stream/TRIAD.hpp"
 #include "stream/TRIAD_PARTED.hpp"
+#include "stream/TRIAD_PARTED_FUSED.hpp"
 #include "stream/DOT.hpp"
 
 //
@@ -218,6 +219,7 @@ static const std::string KernelNames [] =
   std::string("Stream_MUL"),
   std::string("Stream_TRIAD"),
   std::string("Stream_TRIAD_PARTED"),
+  std::string("Stream_TRIAD_PARTED_FUSED"),
 
 //
 // Apps kernels...
@@ -848,6 +850,10 @@ KernelBase* getKernelObject(KernelID kid,
        kernel = new stream::TRIAD_PARTED(run_params);
        break;
     }
+    case Stream_TRIAD_PARTED_FUSED : {
+       kernel = new stream::TRIAD_PARTED_FUSED(run_params);
+       break;
+    }
 
 //
 // Apps kernels...

diff --git a/src/common/RAJAPerfSuite.hpp b/src/common/RAJAPerfSuite.hpp
@@ -136,6 +136,7 @@ enum KernelID {
   Stream_MUL,
   Stream_TRIAD,
   Stream_TRIAD_PARTED,
+  Stream_TRIAD_PARTED_FUSED,
 
 //
 // Apps kernels...

diff --git a/src/stream/CMakeLists.txt b/src/stream/CMakeLists.txt
@@ -44,5 +44,11 @@ blt_add_library(
           TRIAD_PARTED-Cuda.cpp
           TRIAD_PARTED-OMPTarget.cpp
           TRIAD_PARTED-OMP.cpp
+          TRIAD_PARTED_FUSED.cpp
+          TRIAD_PARTED_FUSED-Seq.cpp
+          TRIAD_PARTED_FUSED-Hip.cpp
+          TRIAD_PARTED_FUSED-Cuda.cpp
+          TRIAD_PARTED_FUSED-OMPTarget.cpp
+          TRIAD_PARTED_FUSED-OMP.cpp
   DEPENDS_ON common ${RAJA_PERFSUITE_DEPENDS}
   )
diff --git a/src/stream/TRIAD_PARTED_FUSED-Cuda.cpp b/src/stream/TRIAD_PARTED_FUSED-Cuda.cpp
@@ -0,0 +1,177 @@
+//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
+// Copyright (c) 2017-23, Lawrence Livermore National Security, LLC
+// and RAJA Performance Suite project contributors.
+// See the RAJAPerf/LICENSE file for details.
+//
+// SPDX-License-Identifier: (BSD-3-Clause)
+//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~//
+
+#include "TRIAD_PARTED_FUSED.hpp"
+
+#include "RAJA/RAJA.hpp"
+
+#if defined(RAJA_ENABLE_CUDA)
+
+#include "common/CudaDataUtils.hpp"
+
+#include <iostream>
+
+namespace rajaperf
+{
+namespace stream
+{
+
+#define TRIAD_PARTED_FUSED_MANUAL_FUSER_SETUP_CUDA \
+  Real_ptr*   a_ptrs; \
+  Real_ptr*   b_ptrs; \
+  Real_ptr*   c_ptrs; \
+  Real_type*  alpha_ptrs; \
+  Index_type* ibegin_ptrs; \
+  Index_type* len_ptrs; \
+  allocData(DataSpace::CudaPinned, a_ptrs, parts.size()-1); \
+  allocData(DataSpace::CudaPinned, b_ptrs, parts.size()-1); \
+  allocData(DataSpace::CudaPinned, c_ptrs, parts.size()-1); \
+  allocData(DataSpace::CudaPinned, alpha_ptrs, parts.size()-1); \
+  allocData(DataSpace::CudaPinned, ibegin_ptrs, parts.size()-1); \
+  allocData(DataSpace::CudaPinned, len_ptrs, parts.size()-1);
+
+#define TRIAD_PARTED_FUSED_MANUAL_FUSER_TEARDOWN_CUDA \
+  deallocData(DataSpace::CudaPinned, a_ptrs); \
+  deallocData(DataSpace::CudaPinned, b_ptrs); \
+  deallocData(DataSpace::CudaPinned, c_ptrs); \
+  deallocData(DataSpace::CudaPinned, alpha_ptrs); \
+  deallocData(DataSpace::CudaPinned, ibegin_ptrs); \
+  deallocData(DataSpace::CudaPinned, len_ptrs);
+
+template < size_t block_size >
+__launch_bounds__(block_size)
+__global__ void triad_parted_fused(Real_ptr* a_ptrs, Real_ptr* b_ptrs,
+                                   Real_ptr* c_ptrs, Real_type* alpha_ptrs,
+                                   Index_type* ibegin_ptrs, Index_type* len_ptrs)
+{
+  Index_type j = blockIdx.y;
+
+  Real_ptr   a = a_ptrs[j];
+  Real_ptr   b = b_ptrs[j];
+  Real_ptr   c = c_ptrs[j];
+  Real_type  alpha = alpha_ptrs[j];
+  Index_type ibegin = ibegin_ptrs[j];
+  Index_type iend = ibegin + len_ptrs[j];
+
+  for (Index_type i = ibegin + threadIdx.x + blockIdx.x * block_size;
+       i < iend;
+       i += block_size * gridDim.x) {
+    TRIAD_PARTED_FUSED_BODY;
+  }
+}
+
+
+template < size_t block_size >
+void TRIAD_PARTED_FUSED::runCudaVariantImpl(VariantID vid)
+{
+  const Index_type run_reps = getRunReps();
+
+  auto res{getCudaResource()};
+
+  TRIAD_PARTED_FUSED_DATA_SETUP;
+
+  if ( vid == Base_CUDA ) {
+
+    TRIAD_PARTED_FUSED_MANUAL_FUSER_SETUP_CUDA
+
+    startTimer();
+    for (RepIndex_type irep = 0; irep < run_reps; ++irep) {
+
+      Index_type index = 0;
+      Index_type len_sum = 0;
+
+      for (size_t p = 1; p < parts.size(); ++p ) {
+        const Index_type ibegin = parts[p-1];
+        const Index_type iend = parts[p];
+
+        a_ptrs[index] = a;
+        b_ptrs[index] = b;
+        c_ptrs[index] = c;
+        alpha_ptrs[index] = alpha;
+        ibegin_ptrs[index] = ibegin;
+        len_ptrs[index] = iend-ibegin;
+        len_sum += iend-ibegin;
+        index += 1;
+      }
+      Index_type len_ave = (len_sum + index-1) / index;
+      dim3 nthreads_per_block(block_size);
+      dim3 nblocks((len_ave + block_size-1) / block_size, index);
+      constexpr size_t shmem = 0;
+      triad_parted_fused<block_size><<<nblocks, nthreads_per_block, shmem, res.get_stream()>>>(
+          a_ptrs, b_ptrs, c_ptrs, alpha_ptrs, ibegin_ptrs, len_ptrs);
+      cudaErrchk( cudaGetLastError() );
+      cudaErrchk( cudaStreamSynchronize( res.get_stream() ) );
+
+    }
+    stopTimer();
+
+    TRIAD_PARTED_FUSED_MANUAL_FUSER_TEARDOWN_CUDA
+
+  } else if ( vid == RAJA_CUDA ) {
+
+    using AllocatorHolder = RAJAPoolAllocatorHolder<RAJA::cuda::pinned_mempool_type>;
+    using Allocator = AllocatorHolder::Allocator<char>;
+
+    AllocatorHolder allocatorHolder;
+
+    using workgroup_policy = RAJA::WorkGroupPolicy <
+                                 RAJA::cuda_work_async<block_size>,
+                                 RAJA::unordered_cuda_loop_y_block_iter_x_threadblock_average,
+                                 RAJA::constant_stride_array_of_objects >;
+
+    using workpool = RAJA::WorkPool< workgroup_policy,
+                                     Index_type,
+                                     RAJA::xargs<>,
+                                     Allocator >;
+
+    using workgroup = RAJA::WorkGroup< workgroup_policy,
+                                       Index_type,
+                                       RAJA::xargs<>,
+                                       Allocator >;
+
+    using worksite = RAJA::WorkSite< workgroup_policy,
+                                     Index_type,
+                                     RAJA::xargs<>,
+                                     Allocator >;
+
+    workpool pool(allocatorHolder.template getAllocator<char>());
+    pool.reserve(parts.size()-1, 1024ull*1024ull);
+
+    startTimer();
+    for (RepIndex_type irep = 0; irep < run_reps; ++irep) {
+
+      for (size_t p = 1; p < parts.size(); ++p ) {
+        const Index_type ibegin = parts[p-1];
+        const Index_type iend = parts[p];
+
+        auto triad_parted_fused_lam = [=] __device__ (Index_type i) {
+              TRIAD_PARTED_FUSED_BODY;
+            };
+
+        pool.enqueue(
+            RAJA::TypedRangeSegment<Index_type>(ibegin, iend),
+            triad_parted_fused_lam );
+      }
+      workgroup group = pool.instantiate();
+      worksite site = group.run(res);
+      res.wait();
+
+    }
+    stopTimer();
+
+  } else {
+      getCout() << "\n  TRIAD_PARTED_FUSED : Unknown Cuda variant id = " << vid << std::endl;
+  }
+}
+
+RAJAPERF_GPU_BLOCK_SIZE_TUNING_DEFINE_BOILERPLATE(TRIAD_PARTED_FUSED, Cuda)
+
+} // end namespace stream
+} // end namespace rajaperf
+
+#endif  // RAJA_ENABLE_CUDA