Brandon Potter
288 строки
8.2 KiB
C++
288 строки
8.2 KiB
C++
/********************************************************************************
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* Copyright (c) 2024 Advanced Micro Devices, Inc. All rights reserved.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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* THE SOFTWARE.
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********************************************************************************/
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#ifndef SparseMatrix_H
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#define SparseMatrix_H
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#include "GPUHelper.h"
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#ifndef USE_HIP
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#include "OpenCLHelper.h"
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#include <CL/cl.h>
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#else
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#include "HIPHelper.h"
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#endif
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#include "InputFlags.h"
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#include "MatrixMarketReader.h"
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#include "OpenCLHelper.h"
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#include <algorithm>
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#include <cassert>
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template<typename FloatType>
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class SparseMatrix
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{
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public:
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int nRows;
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int nCols;
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int nNZ;
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int *cols;
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int *row_ptrs;
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FloatType *vals;
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memPointer d_cols;
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memPointer d_vals;
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memPointer d_row_ptrs;
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// info about parallel procs
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int this_pe;
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int total_pes;
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int nRows_p;
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int nCols_p;
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protected:
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GPUHelper *GPU;
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public:
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SparseMatrix() : nRows(0), nCols(0), nNZ(0), nRows_p(0), nCols_p(0)
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{
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cols = NULL;
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row_ptrs = NULL;
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vals = NULL;
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d_cols = NULL;
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d_vals = NULL;
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d_row_ptrs = NULL;
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this_pe = -1;//roc_shmem_my_pe(handle); // this pe
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total_pes = -1;//roc_shmem_n_pes(handle); // total number of pes
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}
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void AllocateSparseMatrix(MatrixMarketReader<FloatType> &mm_reader,
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InputFlags &in_flags,
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GPUHelper *gpu);
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void AllocateParallelSparseMatrix(MatrixMarketReader<FloatType> &mm_reader,
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InputFlags &in_flags);
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void ConvertFromCOOToCSR(Coordinate<FloatType> *coords,
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InputFlags &in_flags);
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void PopulateParallelSparseMatrix(MatrixMarketReader<FloatType> &mm_reader,
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InputFlags &in_flags);
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void FindStatsForParallelDecomposition();
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void Set_total_pes(int val){
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this->total_pes = val;
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}
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void Set_this_pe(int val){
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this->this_pe = val;
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}
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int Get_total_pes(){
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return this->total_pes;
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}
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int Get_this_pe(){
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return this->this_pe;
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}
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int GetNumRows_p() {return nRows_p;}
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int *GetCols() { return cols; }
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FloatType *GetVals() { return vals; }
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int *GetRowPtrs() { return row_ptrs; }
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memPointer GetDevCols() {return d_cols; }
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memPointer GetDevVals() {return d_vals; }
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memPointer GetDevRowPtrs() {return d_row_ptrs; }
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~SparseMatrix()
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{
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delete[] cols;
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delete[] vals;
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delete[] row_ptrs;
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GPU->FreeMem(d_cols);
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GPU->FreeMem(d_vals);
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GPU->FreeMem(d_row_ptrs);
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}
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};
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template<typename FloatType>
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void SparseMatrix<FloatType>::AllocateSparseMatrix(MatrixMarketReader<FloatType> &mm_reader,
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InputFlags &in_flags,
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GPUHelper *gpu)
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{
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GPU = gpu;
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nRows = mm_reader.GetNumRows();
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nCols = mm_reader.GetNumCols();
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nNZ = mm_reader.GetNumNonZeroes();
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printf("Allocating a sparse matrix with-- nRows: %d nCols: %d nNZ: %d\n", nRows, nCols, nNZ);
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assert(total_pes != -1);
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assert(this_pe != -1);
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#ifdef USE_RO_SHMEM
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if (nRows != nCols){
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fprintf(stderr, "RO_SHMEM port requires the global matrix to be "
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"square!\n");
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exit(-1);
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}
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#endif
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cols = new int[nNZ];
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if (cols == NULL)
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{
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fprintf(stderr, "Failed to allocate host-side cols array !\n");
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exit(-1);
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}
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vals = new FloatType[nNZ];
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if (vals == NULL)
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{
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fprintf(stderr, "Failed to allocate host-side vals array !\n");
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exit(-1);
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}
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row_ptrs = new int[nRows + 1];
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if (row_ptrs == NULL)
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{
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fprintf(stderr, "Failed to allocate host-side row_ptrs array !\n");
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exit(-1);
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}
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}
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template<typename FloatType>
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bool CoordinateCompare(const Coordinate<FloatType> &c1, const Coordinate<FloatType> &c2)
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{
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if(c1.x != c2.x)
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return (c1.x < c2.x);
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else
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return (c1.y < c2.y);
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}
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template<typename FloatType>
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void SparseMatrix<FloatType>::ConvertFromCOOToCSR(Coordinate<FloatType> *coords,
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InputFlags &in_flags)
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{
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std::sort(coords, coords + nNZ, CoordinateCompare<FloatType>);
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int current_row = 1;
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bool has_seen_diagonal = false;
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row_ptrs[0] = 0;
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for (int i = 0; i < nNZ; i++)
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{
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cols[i] = coords[i].y;
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vals[i] = coords[i].val;
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//fprintf(stderr,"Row %d Col %d Val %lf (cur_row: %d)\n", coords[i].x, coords[i].y, coords[i].val, current_row-1);
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while(coords[i].x >= current_row)
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{
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// We've reached the end of a row. Did we see a diagonal?
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// If not, the triangular solve will be underconstrained.
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if (!has_seen_diagonal)
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{
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fprintf(stderr, "ERROR Converting the COO to CSR.\n");
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fprintf(stderr, "\tMissing diagonal on row %d\n", current_row-1);
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exit(-1);
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}
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has_seen_diagonal = false;
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row_ptrs[current_row] = i;
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current_row++;
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}
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if (coords[i].x == coords[i].y)
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has_seen_diagonal = true;
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}
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row_ptrs[current_row++] = nNZ;
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while (current_row <= nRows)
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{
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if (!has_seen_diagonal)
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{
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fprintf(stderr, "ERROR Converting the COO to CSR.\n");
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fprintf(stderr, "\tNo values on row %d, so no diagonal.\n", current_row-1);
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exit(-1);
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}
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has_seen_diagonal = false;
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row_ptrs[current_row++] = nNZ;
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}
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}
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template<typename FloatType>
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void SparseMatrix<FloatType>::AllocateParallelSparseMatrix(MatrixMarketReader<FloatType> &mm_reader,
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InputFlags &in_flags)
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{
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d_cols = GPU->AllocateMem("cols", nNZ*sizeof(int), 0, NULL);
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d_vals = GPU->AllocateMem("vals", nNZ*sizeof(FloatType), 0, NULL);
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d_row_ptrs = GPU->AllocateMem("row_ptrs", (nRows+1)*sizeof(int), 0, NULL);
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}
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template<typename FloatType>
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void SparseMatrix<FloatType>::FindStatsForParallelDecomposition()
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{
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assert(SPTS_BLOCK_SIZE % 64 == 0);
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// Rows left over in the potentially partial final block
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int left_over_last_block = nRows % SPTS_BLOCK_SIZE;
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printf("%d: lolb %d\n", this_pe, left_over_last_block);
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// Number of complete blocks, not including any partial block at the end
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int total_blocks = nRows / SPTS_BLOCK_SIZE;
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printf("%d: totb %d\n", this_pe, total_blocks);
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// Everyone has at least this many rows
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nRows_p = (total_blocks / total_pes) * SPTS_BLOCK_SIZE;
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printf("%d: initial nRows_p %d\n", this_pe, nRows_p);
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// Last cycle might not assign to all PEs
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int straggler_blocks = total_blocks % total_pes;
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if (this_pe < straggler_blocks)
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nRows_p += SPTS_BLOCK_SIZE;
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printf("%d: straggler nRows_p %d\n", this_pe, nRows_p);
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// Last block of last cycle might have less than SPTS_BLOCK_SIZE rows
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if (left_over_last_block) {
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int final_pe = ((total_blocks + 1) % total_pes) - 1;
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if (final_pe == -1)
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final_pe = total_pes - 1;
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if (this_pe == final_pe)
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nRows_p += left_over_last_block;
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}
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printf("%d: final nRows_p %d\n", this_pe, nRows_p);
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if (nRows_p <= 0) {
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fprintf(stderr, "Block Size %d too small for input row size %d with "
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"%d number of nodes. Please decrease the block size or "
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"decrease the number of nodes\n", SPTS_BLOCK_SIZE, nRows,
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total_pes);
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exit(-1);
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}
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// print to check!
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printf("\nPE: %d total_rows: %d my_rows: %d\n", this_pe, nRows, nRows_p);
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nCols_p = nCols; // 1D decomposition
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}
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#endif
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