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Minor cleanup

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Chulwoo Jung 2022-11-30 17:13:12 -05:00
parent 82c1ecf60f
commit dc6a38f177
2 changed files with 4 additions and 145 deletions
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145
Grid/algorithms/iterative/ImplicitlyRestartedBlockLanczos.h
View File

@ -7,9 +7,8 @@
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: Chulwoo Jung
Author: Yong-Chull Jang <ypj@quark.phy.bnl.gov>
Author: Guido Cossu
Author: Chulwoo Jung <chulwoo@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@ -185,10 +184,6 @@ public:
{
RealD nn = norm2(v);
nn = sqrt(nn);
#if 0
if(if_print && nn < 1e20)
Glog<<"normalize: "<<nn<<std::endl;
#endif
v = v * (1.0/nn);
return nn;
}
@ -227,19 +222,7 @@ public:
for(int j=0; j<k; ++j){
for(int i=0; i<_Nu; ++i){
ip = innerProduct(evec[j],w[i]);
#if 0
if(if_print)
if( norm(ip)/norm2(w[i]) > 1e-14)
Glog<<"orthogonalize before: "<<i<<" "<<j<<" of "<<k<<" "<< ip <<std::endl;
#endif
w[i] = w[i] - ip * evec[j];
#if 0
if(if_print) {
ip = innerProduct(evec[j],w[i]);
if( norm(ip)/norm2(w[i]) > 1e-14)
Glog<<"orthogonalize after: "<<i<<" "<<j<<" of "<<k<<" "<< ip <<std::endl;
}
#endif
}}
for(int i=0; i<_Nu; ++i)
assert(normalize(w[i],if_print) !=0);
@ -265,14 +248,6 @@ public:
// Glog << "nBatch, Nevec_acc, R, Nu = "
// << Nbatch << "," << Nevec_acc << "," << R << "," << Nu << std::endl;
#if 0 // a trivial test
for (int col=0; col<Nu; ++col) {
for (size_t row=0; row<sites*12; ++row) {
w_acc[col*sites*12+row].x = 1.0;
w_acc[col*sites*12+row].y = 0.0;
}
}
#else
for (int col=0; col<Nu; ++col) {
// auto w_v = w[col].View();
autoView( w_v,w[col], AcceleratorWrite);
@ -282,7 +257,6 @@ public:
w_acc[col*sites*12+row] = z[row];
}
}
#endif
cublasHandle_t handle;
cublasStatus_t stat;
@ -291,14 +265,6 @@ public:
Glog << "cuBLAS Zgemm"<< std::endl;
for (int b=0; b<Nbatch; ++b) {
#if 0 // a trivial test
for (int col=0; col<Nevec_acc; ++col) {
for (size_t row=0; row<sites*12; ++row) {
evec_acc[col*sites*12+row].x = 1.0;
evec_acc[col*sites*12+row].y = 0.0;
}
}
#else
for (int col=0; col<Nevec_acc; ++col) {
// auto evec_v = evec[b*Nevec_acc+col].View();
autoView( evec_v,evec[b*Nevec_acc+col], AcceleratorWrite);
@ -308,7 +274,6 @@ public:
evec_acc[col*sites*12+row] = z[row];
}
}
#endif
CUDA_COMPLEX alpha = MAKE_CUDA_COMPLEX(1.0,0.0);
CUDA_COMPLEX beta = MAKE_CUDA_COMPLEX(0.0,0.0);
stat = CUDA_GEMM(handle, CUBLAS_OP_C, CUBLAS_OP_N, Nevec_acc, Nu, 12*sites,
@ -319,19 +284,6 @@ public:
//Glog << stat << std::endl;
grid->GlobalSumVector((CUDA_FLOAT*)c_acc,2*Nu*Nevec_acc);
#if 0
for (int i=0; i<Nu; ++i) {
for (size_t j=0; j<Nevec_acc; ++j) {
CUDA_COMPLEX z = c_acc[i*Nevec_acc+j];
MyComplex ip(z.x,z.y);
if (do_print) {
Glog << "<evec,w>[" << j << "," << i << "] = "
<< z.x << " + i " << z.y << std::endl;
}
w[i] = w[i] - ip * evec[b*Nevec_acc+j];
}
}
#else
alpha = MAKE_CUDA_COMPLEX(-1.0,0.0);
beta = MAKE_CUDA_COMPLEX(1.0,0.0);
stat = CUDA_GEMM(handle, CUBLAS_OP_N, CUBLAS_OP_N, 12*sites, Nu, Nevec_acc,
@ -340,9 +292,7 @@ public:
&beta,
w_acc, 12*sites);
//Glog << stat << std::endl;
#endif
}
#if 1
for (int col=0; col<Nu; ++col) {
// auto w_v = w[col].View();
autoView( w_v,w[col], AcceleratorWrite);
@ -351,7 +301,6 @@ public:
z[row] = w_acc[col*sites*12+row];
}
}
#endif
for (int i=0; i<Nu; ++i) {
assert(normalize(w[i],do_print)!=0);
}
@ -368,56 +317,6 @@ public:
}
#if 0
void innerProductD (std::vector<ComplexD> &inner, std::vector<Field>& lhs, int llhs, std::vector<Field>& rhs, int lrhs)
{
typedef typename Field:vector_object vobj;
typedef typename vobj::scalar_type scalar_type;
typedef typename vobj::vector_typeD vector_type;
GridBase *grid = lhs[0]._grid;
assert(grid == rhs[0]._grid;
const int pad = 8;
int total = llhs*lrhs;
assert(inner.size()==total);
int sum_size=grid->SumArraySize();
// std::vector<ComplexD> inner(total);
Vector<ComplexD> sumarray(sum_size*pad*total);
parallel_for(int thr=0;thr<sum_size;thr++){
int nwork, mywork, myoff;
GridThread::GetWork(grid->oSites(),thr,mywork,myoff);
std::vector< decltype(innerProductD(lhs[0]._odata[0],rhs[0]._odata[0])) > vinner(total,zero); // private to thread; sub summation
for(int ss=myoff;ss<mywork+myoff; ss++){
for(int i=0; i<llhs; ++i){
for(int j=0; j<lrhs; ++j){
vinner[i*k+j] += innerProductD(lhs[i]._odata[ss],rhs[j]._odata[ss]);
}}
}
// All threads sum across SIMD; reduce serial work at end
// one write per cacheline with streaming store
for(int i=0; i<total; ++i){
ComplexD tmp = Reduce(TensorRemove(vinner[i])) ;
vstream(sumarray[(i*sum_size+thr)*pad],tmp);
}
}
for( int i =0;i<total;i++){
inner[i]=0.0;
for(int j=0;j<sum_size;j++){
inner[i] += sumarray[(i*sum_size+j)*pad];
}
}
for( int i =0;i<total;i++){
ComplexD tmp=inner[i];
evec[0]._grid->GlobalSum(tmp);
inner[i]=tmp;
}
// return inner;
}
#endif
void orthogonalize_blockhead(Field& w, std::vector<Field>& evec, int k, int Nu)
{
@ -839,14 +738,6 @@ cudaStat = cudaMallocManaged((void **)&evec_acc, Nevec_acc*sites*12*sizeof(CUDA_
Glog << fname + " CONVERGED ; Summary :\n";
// Sort convered eigenpairs.
std::vector<Field> Btmp(Nstop,grid); // waste of space replicating
#if 0
for(int i=0; i<Nconv; ++i) Btmp[i]=0;
for(int i=0; i<Nconv; ++i)
for(int k = 0; k<Nr; ++k){
Btmp[i].Checkerboard() = evec[k].Checkerboard();
Btmp[i] += evec[k]*Qt(k,i);
}
#endif
for(int i=0; i<Nstop; ++i){
Btmp[i]=0.;
@ -1021,25 +912,6 @@ if(split_test){
}
}
Glog << "LinAlg done "<< std::endl;
#if 0
Glog << "Gram Schmidt "<< std::endl;
// re-orthogonalization for numerical stability
if (b>0) {
for (int u=0; u<Nu; ++u) {
orthogonalize(w[u],evec,R);
}
for (int u=1; u<Nu; ++u) {
orthogonalize(w[u],w,u);
}
}
//if (b>0) {
// orthogonalize_blockhead(w[0],evec,b,Nu);
// for (int u=1; u<Nu; ++u) {
// orthogonalize(w[u],w,u);
// }
//}
Glog << "Gram Schmidt done "<< std::endl;
#endif
if (b < Nm/Nu-1) {
for (int u=0; u<Nu; ++u) {
@ -1118,7 +990,6 @@ if(split_test){
}
//std::cout << BlockTriDiag << std::endl;
//#ifdef USE_LAPACK
#if 1
const int size = Nm;
MKL_INT NN = Nk;
// double evals_tmp[NN];
@ -1189,20 +1060,6 @@ if(split_test){
grid->GlobalSumVector((double*)evec_tmp,2*NN*NN);
}
}
// Safer to sort instead of just reversing it,
// but the document of the routine says evals are sorted in increasing order.
// qr gives evals in decreasing order.
// for(int i=0;i<NN;i++){
// lmd [NN-1-i]=evals_tmp[i];
// for(int j=0;j<NN;j++){
// Qt((NN-1-i),j)=evec_tmp[i][j];
// }
// }
// MKL_Complex16 *eval_tmp = malloc(NN*sizeof(MKL_Complex16));
// MKL_Complex16 *evec_tmp = malloc(NN*NN*sizeof(MKL_Complex16));
// MKL_Complex16 *DD = malloc(NN*NN*sizeof(MKL_Complex16));
#endif
for (int i = 0; i < Nk; i++)
eval[Nk-1-i] = evals_tmp[i];
for (int i = 0; i < Nk; i++) {

4
tests/lanczos/Test_dwf_block_lanczos.cc
View File

@ -4,9 +4,11 @@
Source file: ./tests/Test_dwf_block_lanczos.cc
Copyright (C) 2015
Copyright (C) 2022
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
Author: Yong-Chull Jang <ypj@quark.phy.bnl.gov>
Author: Chulwoo Jung <chulwoo@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by