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Adding sliceSumReduction_cub_small/large since hipcub cannot deal with arb. large vobjs
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@ -1,4 +1,5 @@
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#pragma once
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#include <type_traits>
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#if defined(GRID_CUDA)
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#include <cub/cub.cuh>
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@ -26,20 +27,16 @@
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NAMESPACE_BEGIN(Grid);
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#if defined(GRID_CUDA) || defined(GRID_HIP)
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template<class vobj> inline void sliceSumReduction_cub(const Lattice<vobj> &Data, Vector<vobj> &lvSum, const int rd, const int e1, const int e2, const int stride, const int ostride, const int Nsimd)
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{
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typedef typename vobj::scalar_object sobj;
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template<class vobj> inline void sliceSumReduction_cub_small(const vobj *Data, Vector<vobj> &lvSum, const int rd, const int e1, const int e2, const int stride, const int ostride, const int Nsimd) {
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size_t subvol_size = e1*e2;
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commVector<vobj> reduction_buffer(rd*subvol_size);
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auto rb_p = &reduction_buffer[0];
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vobj zero_init;
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zeroit(zero_init);
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vobj vobj_zero; //Need to provide initial value for reduction operation
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zeroit(vobj_zero);
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void *temp_storage_array = NULL;
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size_t temp_storage_bytes = 0;
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vobj *d_out;
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@ -71,8 +68,8 @@ template<class vobj> inline void sliceSumReduction_cub(const Lattice<vobj> &Data
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exit(EXIT_FAILURE);
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}
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//determine temp_storage_array size
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gpuErr = gpucub::DeviceSegmentedReduce::Reduce(temp_storage_array, temp_storage_bytes, rb_p,d_out, rd, d_offsets, d_offsets+1, ::gpucub::Sum(), vobj_zero, computeStream);
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gpuErr = gpucub::DeviceSegmentedReduce::Reduce(temp_storage_array, temp_storage_bytes, rb_p,d_out, rd, d_offsets, d_offsets+1, ::gpucub::Sum(), zero_init, computeStream);
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if (gpuErr!=gpuSuccess) {
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std::cout << GridLogError << "Lattice_slicesum_gpu.h: Encountered error during gpucub::DeviceSegmentedReduce::Reduce (setup)! Error: " << gpuErr <<std::endl;
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exit(EXIT_FAILURE);
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@ -85,11 +82,9 @@ template<class vobj> inline void sliceSumReduction_cub(const Lattice<vobj> &Data
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exit(EXIT_FAILURE);
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}
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autoView( Data_v, Data, AcceleratorRead);
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//prepare buffer for reduction
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//use non-blocking accelerator_for to avoid syncs (ok because we submit to same computeStream)
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//use 2d accelerator_for to avoid launch latencies found when serially looping over rd
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accelerator_for2dNB( s,subvol_size, r,rd, Nsimd,{
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int n = s / e2;
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@ -97,12 +92,12 @@ template<class vobj> inline void sliceSumReduction_cub(const Lattice<vobj> &Data
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int so=r*ostride; // base offset for start of plane
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int ss= so+n*stride+b;
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coalescedWrite(rb_p[r*subvol_size+s], coalescedRead(Data_v[ss]));
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coalescedWrite(rb_p[r*subvol_size+s], coalescedRead(Data[ss]));
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});
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//issue segmented reductions in computeStream
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gpuErr = gpucub::DeviceSegmentedReduce::Reduce(temp_storage_array, temp_storage_bytes, rb_p, d_out, rd, d_offsets, d_offsets+1,::gpucub::Sum(), vobj_zero, computeStream);
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gpuErr = gpucub::DeviceSegmentedReduce::Reduce(temp_storage_array, temp_storage_bytes, rb_p, d_out, rd, d_offsets, d_offsets+1,::gpucub::Sum(), zero_init, computeStream);
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if (gpuErr!=gpuSuccess) {
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std::cout << GridLogError << "Lattice_slicesum_gpu.h: Encountered error during gpucub::DeviceSegmentedReduce::Reduce! Error: " << gpuErr <<std::endl;
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exit(EXIT_FAILURE);
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@ -119,6 +114,48 @@ template<class vobj> inline void sliceSumReduction_cub(const Lattice<vobj> &Data
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}
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template<class vobj> inline void sliceSumReduction_cub_large(const vobj *Data, Vector<vobj> &lvSum, const int rd, const int e1, const int e2, const int stride, const int ostride, const int Nsimd) {
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typedef typename vobj::vector_type vector;
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const int words = sizeof(vobj)/sizeof(vector);
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const int osites = rd*e1*e2;
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Vector<vector>buffer(osites);
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vector *dat = (vector *)Data;
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vector *buf = &buffer[0];
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Vector<vector> lvSum_small(rd);
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vector *lvSum_ptr = (vector *)&lvSum[0];
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for (int w = 0; w < words; w++) {
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accelerator_for(ss,osites,1,{
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buf[ss] = dat[ss*words+w];
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});
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sliceSumReduction_cub_small(buf,lvSum_small,rd,e1,e2,stride, ostride,Nsimd);
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for (int r = 0; r < rd; r++) {
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lvSum_ptr[w+words*r]=lvSum_small[r];
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}
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}
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}
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template<class vobj> inline void sliceSumReduction_cub(const Lattice<vobj> &Data, Vector<vobj> &lvSum, const int rd, const int e1, const int e2, const int stride, const int ostride, const int Nsimd)
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{
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autoView(Data_v, Data, AcceleratorRead);
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#if defined(GRID_CUDA)
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sliceSumReduction_cub_small(&Data_v[0], lvSum, rd, e1, e2, stride, ostride, Nsimd);
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#elif defined (GRID_HIP) //hipcub cannot deal with large vobjs that don't fit in shared memory, therefore separate into _small/_large.
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if constexpr (sizeof(vobj) <= 256) {
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sliceSumReduction_cub_small(&Data_v[0], lvSum, rd, e1, e2, stride, ostride, Nsimd);
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}
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else {
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sliceSumReduction_cub_large(&Data_v[0], lvSum, rd, e1, e2, stride, ostride, Nsimd);
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}
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#endif
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}
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#endif
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