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https://github.com/paboyle/Grid.git
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block Lanczos cublas buffer is set at the inital step; buffer width is fixed to the block size then cublas Zgemm is called multiple times
This commit is contained in:
Yong-Chull Jang
parent
02edbe624f
commit
ac7090e6d3
@ -110,7 +110,7 @@ private:
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std::string cname = std::string("ImplicitlyRestartedBlockLanczos");
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int MaxIter; // Max iterations
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int Nstop; // Number of evecs checked for convergence
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int Nu; // Numbeer of vecs in the unit block
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int Nu; // Number of vecs in the unit block
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int Nk; // Number of converged sought
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int Nm; // total number of vectors
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int Nblock_k; // Nk/Nu
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@ -129,7 +129,15 @@ private:
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GridRedBlackCartesian * f_grid;
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GridRedBlackCartesian * sf_grid;
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int mrhs;
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/////////////////////////
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// BLAS objects
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/////////////////////////
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#ifdef GRID_NVCC
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cudaError_t cudaStat;
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cuDoubleComplex *w_acc, *evec_acc, *c_acc;
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#endif
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int Nevec_acc; // Number of eigenvectors stored in the buffer evec_acc
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/////////////////////////
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// Constructor
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/////////////////////////
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@ -154,7 +162,8 @@ public:
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Nblock_m(_Nm/_Nu), Nblock_k(_Nk/_Nu),
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//eresid(_eresid), MaxIter(10),
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eresid(_eresid), MaxIter(_MaxIter),
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diagonalisation(_diagonalisation),split_test(0)
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diagonalisation(_diagonalisation),split_test(0),
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Nevec_acc(_Nu)
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{ assert( (Nk%Nu==0) && (Nm%Nu==0) ); };
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////////////////////////////////
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@ -225,7 +234,7 @@ public:
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}
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void orthogonalize_blas(std::vector<Field>& w, int _Nu, std::vector<Field>& evec, int _R, int _print=0)
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void orthogonalize_blas(std::vector<Field>& w, std::vector<Field>& evec, int R, int do_print=0)
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{
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#ifdef GRID_NVCC
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Glog << "cuBLAS orthogonalize" << std::endl;
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@ -237,105 +246,86 @@ public:
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typedef typename Field::scalar_type MyComplex;
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GridBase *grid = w[0].Grid();
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//grid->show_decomposition();
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//const uint64_t nsimd = grid->Nsimd();
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const uint64_t sites = grid->lSites();
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//auto w_v = w[0].View();
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//cuDoubleComplex *z = reinterpret_cast<cuDoubleComplex*>(&w_v._odata[0]);
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//cuDoubleComplex *z = w_v._odata._internal;
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//thread_for(ss,w_v.size(),{
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// Glog << w_v[ss] << std::endl;
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//});
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//w_v[0]
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//exit(0);
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//scalar_type *z = (scalar_type *)&w_v[0]; // OK
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//cuDoubleComplex *z = reinterpret_cast<cuDoubleComplex *>(&w_v[0]); // OK
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cudaError_t cudaStat;
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int Nbatch = R/Nevec_acc;
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assert( R%Nevec_acc == 0 );
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Glog << "nBatch, Nevec_acc, R, Nu = "
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<< Nbatch << "," << Nevec_acc << "," << R << "," << Nu << std::endl;
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cuDoubleComplex *w_acc, *evec_acc, *c_acc;
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cudaStat = cudaMallocManaged((void **)&w_acc, _Nu*sites*12*sizeof(cuDoubleComplex));
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Glog << cudaStat << std::endl;
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cudaStat = cudaMallocManaged((void **)&evec_acc, _R*sites*12*sizeof(cuDoubleComplex));
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Glog << cudaStat << std::endl;
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cudaStat = cudaMallocManaged((void **)&c_acc, _Nu*_R*12*sizeof(cuDoubleComplex));
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Glog << cudaStat << std::endl;
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Glog << "cuBLAS prepare array"<< std::endl;
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#if 0 // a trivial test
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for (int col=0; col<_Nu; ++col) {
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for (int col=0; col<Nu; ++col) {
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for (size_t row=0; row<sites*12; ++row) {
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w_acc[col*sites*12+row].x = 1.0;
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w_acc[col*sites*12+row].y = 0.0;
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}
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}
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for (int col=0; col<_R; ++col) {
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for (size_t row=0; row<sites*12; ++row) {
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evec_acc[col*sites*12+row].x = 1.0;
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evec_acc[col*sites*12+row].y = 0.0;
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}
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}
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#else
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for (int col=0; col<_Nu; ++col) {
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for (int col=0; col<Nu; ++col) {
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auto w_v = w[col].View();
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cuDoubleComplex *z = reinterpret_cast<cuDoubleComplex*>(&w_v[0]);
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for (size_t row=0; row<sites*12; ++row) {
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//w_acc[col*sites*12+row].x = z[2*row];
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//w_acc[col*sites*12+row].y = z[2*row+1];
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w_acc[col*sites*12+row] = z[row];
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}
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}
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for (int col=0; col<_R; ++col) {
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auto evec_v = evec[col].View();
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cuDoubleComplex *z = reinterpret_cast<cuDoubleComplex*>(&evec_v[0]);
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for (size_t row=0; row<sites*12; ++row) {
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//evec_acc[col*sites*12+row].x = z[2*row];
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//evec_acc[col*sites*12+row].y = z[2*row+1];
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evec_acc[col*sites*12+row] = z[row];
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}
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}
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#endif
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Glog << "cuBLAS prepare array done"<< std::endl;
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Glog << "cuBLAS Zgemm"<< std::endl;
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#endif
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cublasHandle_t handle;
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cublasStatus_t stat;
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stat = cublasCreate(&handle);
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cuDoubleComplex alpha = make_cuDoubleComplex(1.0,0.0);
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cuDoubleComplex beta = make_cuDoubleComplex(0.0,0.0);
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stat = cublasZgemm(handle, CUBLAS_OP_C, CUBLAS_OP_N, _R, _Nu, 12*sites,
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&alpha, evec_acc, 12*sites, w_acc, 12*sites, &beta, c_acc, _R);
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Glog << stat << std::endl;
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grid->GlobalSumVector((double*)c_acc,2*_Nu*_R);
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cublasDestroy(handle);
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Glog << "cuBLAS Zgemm"<< std::endl;
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for (int b=0; b<Nbatch; ++b) {
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#if 0 // a trivial test
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for (int col=0; col<Nevec_acc; ++col) {
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for (size_t row=0; row<sites*12; ++row) {
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evec_acc[col*sites*12+row].x = 1.0;
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evec_acc[col*sites*12+row].y = 0.0;
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}
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}
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#else
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for (int col=0; col<Nevec_acc; ++col) {
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auto evec_v = evec[b*Nevec_acc+col].View();
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cuDoubleComplex *z = reinterpret_cast<cuDoubleComplex*>(&evec_v[0]);
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for (size_t row=0; row<sites*12; ++row) {
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evec_acc[col*sites*12+row] = z[row];
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}
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}
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#endif
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cuDoubleComplex alpha = make_cuDoubleComplex(1.0,0.0);
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cuDoubleComplex beta = make_cuDoubleComplex(0.0,0.0);
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stat = cublasZgemm(handle, CUBLAS_OP_C, CUBLAS_OP_N, Nevec_acc, Nu, 12*sites,
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&alpha,
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evec_acc, 12*sites, w_acc, 12*sites,
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&beta,
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c_acc, Nevec_acc);
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//Glog << stat << std::endl;
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grid->GlobalSumVector((double*)c_acc,2*Nu*Nevec_acc);
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for (int i=0; i<Nu; ++i) {
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for (size_t j=0; j<Nevec_acc; ++j) {
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cuDoubleComplex z = c_acc[i*Nevec_acc+j];
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MyComplex ip(z.x,z.y);
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if (do_print) {
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Glog << "<evec,w>[" << j << "," << i << "] = "
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<< z.x << " + i " << z.y << std::endl;
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}
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w[i] = w[i] - ip * evec[b*Nevec_acc+j];
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}
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//assert(normalize(w[i],do_print)!=0);
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}
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}
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for (int i=0; i<Nu; ++i) {
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assert(normalize(w[i],do_print)!=0);
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}
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Glog << "cuBLAS Zgemm done"<< std::endl;
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for (int i=0; i<_Nu; ++i) {
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for (size_t j=0; j<_R; ++j) {
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cuDoubleComplex z = c_acc[i*_R+j];
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MyComplex ip(z.x,z.y);
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if (_print) {
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Glog << "<evec,w>[" << j << "," << i << "] = "
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<< z.x << " + i " << z.y << std::endl;
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}
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w[i] = w[i] - ip * evec[j];
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}
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assert(normalize(w[i],_print)!=0);
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}
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cublasDestroy(handle);
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cudaFree(w_acc);
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cudaFree(evec_acc);
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cudaFree(c_acc);
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Glog << "cuBLAS orthogonalize done" << std::endl;
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#else
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Glog << "BLAS wrapper is not implemented" << std::endl;
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@ -411,6 +401,21 @@ for( int i =0;i<total;i++){
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std::vector<Field>& evec,
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const std::vector<Field>& src, int& Nconv, LanczosType Impl)
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{
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#ifdef GRID_NVCC
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GridBase *grid = src[0].Grid();
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grid->show_decomposition();
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// set eigenvector buffers for the cuBLAS calls
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//const uint64_t nsimd = grid->Nsimd();
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const uint64_t sites = grid->lSites();
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cudaStat = cudaMallocManaged((void **)&w_acc, Nu*sites*12*sizeof(cuDoubleComplex));
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//Glog << cudaStat << std::endl;
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cudaStat = cudaMallocManaged((void **)&evec_acc, Nevec_acc*sites*12*sizeof(cuDoubleComplex));
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//Glog << cudaStat << std::endl;
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cudaStat = cudaMallocManaged((void **)&c_acc, Nu*Nevec_acc*sizeof(cuDoubleComplex));
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//Glog << cudaStat << std::endl;
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#endif
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switch (Impl) {
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case LanczosType::irbl:
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calc_irbl(eval,evec,src,Nconv);
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@ -420,6 +425,12 @@ for( int i =0;i<total;i++){
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calc_rbl(eval,evec,src,Nconv);
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break;
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}
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#ifdef GRID_NVCC
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// free eigenvector buffers for the cuBLAS calls
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cudaFree(w_acc);
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cudaFree(evec_acc);
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cudaFree(c_acc);
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#endif
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}
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void calc_irbl(std::vector<RealD>& eval,
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@ -919,8 +930,8 @@ if(!split_test){
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orthogonalize(w[u],evec,R);
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}
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#else
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//orthogonalize(w,Nu,evec,R);
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orthogonalize_blas(w,Nu,evec,R);
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//orthogonalize(w,Nu,evec,R);
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orthogonalize_blas(w,evec,R);
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#endif
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// QR part
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for (int u=1; u<Nu; ++u) {
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