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BlockCG linalg via BLAS
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Peter Boyle
parent
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249
Grid/algorithms/deflation/MultiRHSBlockCGLinalg.h
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249
Grid/algorithms/deflation/MultiRHSBlockCGLinalg.h
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/*************************************************************************************
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Grid physics library, www.github.com/paboyle/Grid
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Source file: MultiRHSBlockCGLinalg.h
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Copyright (C) 2024
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Author: Peter Boyle <pboyle@bnl.gov>
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This program is free software; you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation; either version 2 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License along
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with this program; if not, write to the Free Software Foundation, Inc.,
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51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
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See the full license in the file "LICENSE" in the top level distribution directory
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*************************************************************************************/
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/* END LEGAL */
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#pragma once
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NAMESPACE_BEGIN(Grid);
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/* Need helper object for BLAS accelerated mrhs blockCG */
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template<class Field>
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class MultiRHSBlockCGLinalg
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{
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public:
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typedef typename Field::scalar_type scalar;
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typedef typename Field::scalar_object scalar_object;
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deviceVector<scalar> BLAS_X; // nrhs x vol -- the sources
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deviceVector<scalar> BLAS_Y; // nrhs x vol -- the result
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deviceVector<scalar> BLAS_C; // nrhs x nrhs -- the coefficients
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MultiRHSBlockCGLinalg() {};
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~MultiRHSBlockCGLinalg(){ Deallocate(); };
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void Deallocate(void)
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{
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BLAS_C.resize(0);
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BLAS_X.resize(0);
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BLAS_Y.resize(0);
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}
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void MaddMatrix(std::vector<Field> &AP, Eigen::MatrixXcd &m , const std::vector<Field> &X,const std::vector<Field> &Y,RealD scale=1.0)
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{
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std::vector<Field> Y_copy(AP.size(),AP[0].Grid());
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for(int r=0;r<AP.size();r++){
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Y_copy[r] = Y[r];
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}
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MulMatrix(AP,m,X);
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for(int r=0;r<AP.size();r++){
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AP[r] = scale*AP[r]+Y_copy[r];
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}
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}
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void MulMatrix(std::vector<Field> &Y, Eigen::MatrixXcd &m , const std::vector<Field> &X)
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{
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typedef typename Field::scalar_type scomplex;
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GridBase *grid;
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uint64_t vol;
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uint64_t words;
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int nrhs = Y.size();
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grid = X[0].Grid();
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vol = grid->lSites();
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words = sizeof(scalar_object)/sizeof(scalar);
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int64_t vw = vol * words;
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RealD t0 = usecond();
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BLAS_X.resize(nrhs * vw); // cost free if size doesn't change
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BLAS_Y.resize(nrhs * vw); // cost free if size doesn't change
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BLAS_C.resize(nrhs * nrhs);// cost free if size doesn't change
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RealD t1 = usecond();
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/////////////////////////////////////////////
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// Copy in the multi-rhs sources
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/////////////////////////////////////////////
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for(int r=0;r<nrhs;r++){
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int64_t offset = r*vw;
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autoView(x_v,X[r],AcceleratorRead);
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acceleratorCopyDeviceToDevice(&x_v[0],&BLAS_X[offset],sizeof(scalar_object)*vol);
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}
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// Assumes Eigen storage contiguous
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acceleratorCopyToDevice(&m(0,0),&BLAS_C[0],BLAS_C.size()*sizeof(scalar));
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/*
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* in Fortran column major notation (cuBlas order)
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*
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* Xxr = [X1(x)][..][Xn(x)]
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* Yxr = [Y1(x)][..][Ym(x)]
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* Y = X . C
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*/
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deviceVector<scalar *> Xd(1);
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deviceVector<scalar *> Yd(1);
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deviceVector<scalar *> Cd(1);
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scalar * Xh = & BLAS_X[0];
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scalar * Yh = & BLAS_Y[0];
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scalar * Ch = & BLAS_C[0];
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acceleratorPut(Xd[0],Xh);
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acceleratorPut(Yd[0],Yh);
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acceleratorPut(Cd[0],Ch);
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RealD t2 = usecond();
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GridBLAS BLAS;
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/////////////////////////////////////////
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// Y = X*C (transpose?)
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/////////////////////////////////////////
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BLAS.gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
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vw,nrhs,nrhs,
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ComplexD(1.0),
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Xd,
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Cd,
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ComplexD(0.0), // wipe out Y
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Yd);
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BLAS.synchronise();
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RealD t3 = usecond();
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// Copy back Y = m X
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for(int r=0;r<nrhs;r++){
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int64_t offset = r*vw;
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autoView(y_v,Y[r],AcceleratorWrite);
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acceleratorCopyDeviceToDevice(&BLAS_Y[offset],&y_v[0],sizeof(scalar_object)*vol);
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}
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RealD t4 = usecond();
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std::cout << "MulMatrix alloc took "<< t1-t0<<" us"<<std::endl;
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std::cout << "MulMatrix preamble took "<< t2-t1<<" us"<<std::endl;
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std::cout << "MulMatrix blas took "<< t3-t2<<" us"<<std::endl;
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std::cout << "MulMatrix copy took "<< t4-t3<<" us"<<std::endl;
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std::cout << "MulMatrix total "<< t4-t0<<" us"<<std::endl;
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}
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void InnerProductMatrix(Eigen::MatrixXcd &m , const std::vector<Field> &X, const std::vector<Field> &Y)
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{
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int nrhs;
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GridBase *grid;
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uint64_t vol;
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uint64_t words;
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nrhs = X.size();
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assert(X.size()==Y.size());
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conformable(X[0],Y[0]);
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grid = X[0].Grid();
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vol = grid->lSites();
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words = sizeof(scalar_object)/sizeof(scalar);
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int64_t vw = vol * words;
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RealD t0 = usecond();
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BLAS_X.resize(nrhs * vw); // cost free if size doesn't change
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BLAS_Y.resize(nrhs * vw); // cost free if size doesn't change
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BLAS_C.resize(nrhs * nrhs);// cost free if size doesn't change
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RealD t1 = usecond();
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/////////////////////////////////////////////
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// Copy in the multi-rhs sources
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/////////////////////////////////////////////
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for(int r=0;r<nrhs;r++){
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int64_t offset = r*vw;
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autoView(x_v,X[r],AcceleratorRead);
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acceleratorCopyDeviceToDevice(&x_v[0],&BLAS_X[offset],sizeof(scalar_object)*vol);
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autoView(y_v,Y[r],AcceleratorRead);
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acceleratorCopyDeviceToDevice(&y_v[0],&BLAS_Y[offset],sizeof(scalar_object)*vol);
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}
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RealD t2 = usecond();
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/*
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* in Fortran column major notation (cuBlas order)
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*
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* Xxr = [X1(x)][..][Xn(x)]
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*
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* Yxr = [Y1(x)][..][Ym(x)]
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*
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* C_rs = X^dag Y
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*/
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deviceVector<scalar *> Xd(1);
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deviceVector<scalar *> Yd(1);
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deviceVector<scalar *> Cd(1);
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scalar * Xh = & BLAS_X[0];
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scalar * Yh = & BLAS_Y[0];
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scalar * Ch = & BLAS_C[0];
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acceleratorPut(Xd[0],Xh);
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acceleratorPut(Yd[0],Yh);
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acceleratorPut(Cd[0],Ch);
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GridBLAS BLAS;
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RealD t3 = usecond();
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/////////////////////////////////////////
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// C_rs = X^dag Y
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/////////////////////////////////////////
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BLAS.gemmBatched(GridBLAS_OP_C,GridBLAS_OP_N,
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nrhs,nrhs,vw,
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ComplexD(1.0),
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Xd,
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Yd,
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ComplexD(0.0), // wipe out C
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Cd);
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BLAS.synchronise();
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RealD t4 = usecond();
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std::vector<scalar> HOST_C(BLAS_C.size()); // nrhs . nrhs -- the coefficients
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acceleratorCopyFromDevice(&BLAS_C[0],&HOST_C[0],BLAS_C.size()*sizeof(scalar));
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grid->GlobalSumVector(&HOST_C[0],nrhs*nrhs);
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RealD t5 = usecond();
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for(int rr=0;rr<nrhs;rr++){
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for(int r=0;r<nrhs;r++){
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int off = r+nrhs*rr;
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m(r,rr)=HOST_C[off];
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}
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}
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RealD t6 = usecond();
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uint64_t M=nrhs;
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uint64_t N=nrhs;
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uint64_t K=vw;
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RealD bytes = 1.0*sizeof(ComplexD)*(M*N*2+N*K+M*K);
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RealD flops = 8.0*M*N*K;
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flops = flops/(t4-t3)/1.e3;
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bytes = bytes/(t4-t3)/1.e3;
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std::cout << "InnerProductMatrix m,n,k "<< M<<","<<N<<","<<K<<std::endl;
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std::cout << "InnerProductMatrix alloc t1 "<< t1-t0<<" us"<<std::endl;
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std::cout << "InnerProductMatrix cp t2 "<< t2-t1<<" us"<<std::endl;
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std::cout << "InnerProductMatrix setup t3 "<< t3-t2<<" us"<<std::endl;
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std::cout << "InnerProductMatrix blas t4 "<< t4-t3<<" us"<<std::endl;
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std::cout << "InnerProductMatrix blas "<< flops<<" GF/s"<<std::endl;
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std::cout << "InnerProductMatrix blas "<< bytes<<" GB/s"<<std::endl;
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std::cout << "InnerProductMatrix gsum t5 "<< t5-t4<<" us"<<std::endl;
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std::cout << "InnerProductMatrix cp t6 "<< t6-t5<<" us"<<std::endl;
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std::cout << "InnerProductMatrix took "<< t6-t0<<" us"<<std::endl;
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}
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};
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NAMESPACE_END(Grid);
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