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31 Commits

Author SHA1 Message Date
Ed Bennett
04b3fbcd6d
Merge 32e6d58356 into aa67a5b095 2024-09-04 13:38:28 +01:00
Peter Boyle
aa67a5b095 Rename 2024-08-27 19:54:01 +00:00
Peter Boyle
af9ea0864c Blas fix 2024-08-27 19:53:09 +00:00
Peter Boyle
4e2a6d87c4 Gemm batched fix 2024-08-27 19:24:05 +00:00
Peter Boyle
a465ecece9 Aurora 2024-08-27 19:20:43 +00:00
Peter Boyle
575eb72182 Converges on 16^3 2024-08-27 19:20:38 +00:00
Peter Boyle
3a973914d6 Compile on frontier 2024-08-27 14:55:42 -04:00
Peter Boyle
f568c07bbd Improved the BLAS benchmark 2024-08-27 14:53:54 -04:00
Peter Boyle
2c9878fc3a Merge branch 'develop' of https://github.com/paboyle/Grid into develop 2024-08-27 12:05:46 -04:00
Peter Boyle
27b1b1b005 Checkerboard available for offloading pickCheckerboard 2024-08-27 12:04:09 -04:00
Peter Boyle
130d7ab077 Verbose changes 2024-08-27 12:03:28 -04:00
Peter Boyle
29f6b8a74a Setup 2024-08-27 12:02:49 -04:00
Peter Boyle
9779aaea33 16^3 optimise 2024-08-27 11:38:35 -04:00
Peter Boyle
ec25604a67 Fastest solver for mrhs multigrid 2024-08-27 11:32:34 -04:00
Peter Boyle
3668e81c5e Extract slice working on checkerboard field for Block Lanczos 2024-08-27 11:31:30 -04:00
Peter Boyle
d66b2423cb Move slice operations to GPU for BlockCG 2024-08-27 11:28:47 -04:00
Peter Boyle
15cc78f0b6 peek/poke local site on checkerboard arrays 2024-08-27 11:23:42 -04:00
Peter Boyle
06db4ddea2 Fast init on GPU 2024-08-27 11:22:33 -04:00
Peter Boyle
6cfb90e99f Support needed for accelerator resident set/pick Checkerboard 2024-08-27 11:19:00 -04:00
Peter Boyle
d8be95a2a3 Don't early terminate power method to get more accurate top EV 2024-08-27 11:17:37 -04:00
Peter Boyle
f82702872d Normal residual 2024-08-27 11:16:44 -04:00
Peter Boyle
3752c49ef0 Add option to record the CG polynomial 2024-08-27 11:14:35 -04:00
Peter Boyle
fe65fa4988 MulMatrix 2024-08-27 11:13:18 -04:00
Peter Boyle
1fe4c205a3 Adef 2024-08-27 11:11:47 -04:00
Peter Boyle
d4dc5e0f43 BlockCG linalg acceleratoin with BLAS 2024-08-27 11:08:33 -04:00
Peter Boyle
77944437ce Functor initialisation 2024-08-27 11:01:02 -04:00
Peter Boyle
c164bff758 MMdag 2024-08-27 11:00:36 -04:00
Peter Boyle
aa2e3d954a MMdag operator 2024-08-27 10:59:29 -04:00
Peter Boyle
de62b04728 Block CG linalg acceleration 2024-08-27 10:58:54 -04:00
Peter Boyle
d0bdb50f24 Analyse power spectrum 2024-08-27 10:58:19 -04:00
Peter Boyle
a8fecbc609 BlockCG linalg via BLAS 2024-08-21 16:08:16 -04:00
30 changed files with 2416 additions and 634 deletions

View File

@ -12,15 +12,13 @@
#include <iostream>
#include <sys/time.h>
#define GRID_SYCL
#undef GRID_HIP
#undef GRID_CUDA
#ifdef GRID_HIP
#include <hipblas/hipblas.h>
#endif
#ifdef GRID_CUDA
#include <cublas_v2.h>
#endif
#ifdef GRID_SYCL
#include <oneapi/mkl.hpp>
@ -45,6 +43,90 @@ inline void acceleratorFreeDevice(void *ptr,size_t bytes){free(ptr,*theAccelerat
inline void acceleratorMemSet(void *base,int value,size_t bytes) { theAccelerator->memset(base,value,bytes); theAccelerator->wait();}
inline void acceleratorCopyToDevice(void *from,void *to,size_t bytes) { theAccelerator->memcpy(to,from,bytes); theAccelerator->wait();}
inline void acceleratorCopyFromDevice(void *from,void *to,size_t bytes){ theAccelerator->memcpy(to,from,bytes); theAccelerator->wait();}
#define accelerator_barrier(dummy) { theAccelerator->wait(); }
#endif
#ifdef GRID_HIP
hipStream_t copyStream;
hipStream_t computeStream;
void acceleratorInit(void)
{
int device = 0;
auto discard = hipSetDevice(device);
discard = hipStreamCreate(&copyStream);
discard = hipStreamCreate(&computeStream);
printf("AcceleratorHIPInit\n");
}
inline void *acceleratorAllocDevice(size_t bytes)
{
void *ptr=NULL;
auto err = hipMalloc((void **)&ptr,bytes);
if( err != hipSuccess ) {
ptr = (void *) NULL;
fprintf(stderr," hipMalloc failed for %ld %s \n",bytes,hipGetErrorString(err)); fflush(stderr);
}
return ptr;
};
inline void acceleratorFreeDevice(void *ptr,size_t bytes){ auto discard=hipFree(ptr);};
inline void acceleratorFreeDevice(void *ptr){ auto discard=hipFree(ptr);};
inline void acceleratorMemSet(void *base,int value,size_t bytes) { auto discard=hipMemset(base,value,bytes);}
inline void acceleratorCopyToDevice(void *from,void *to,size_t bytes) { auto discard=hipMemcpy(to,from,bytes, hipMemcpyHostToDevice);}
inline void acceleratorCopyFromDevice(void *from,void *to,size_t bytes){ auto discard=hipMemcpy(to,from,bytes, hipMemcpyDeviceToHost);}
#define accelerator_barrier(dummy) \
{ \
auto tmp=hipStreamSynchronize(computeStream); \
auto err = hipGetLastError(); \
if ( err != hipSuccess ) { \
printf("After hipDeviceSynchronize() : HIP error %s \n", hipGetErrorString( err )); \
puts(__FILE__); \
printf("Line %d\n",__LINE__); \
exit(0); \
} \
}
#endif
#ifdef GRID_CUDA
cudaStream_t copyStream;
cudaStream_t computeStream;
void acceleratorInit(void)
{
int device = 0;
cudaSetDevice(device);
cudaStreamCreate(&copyStream);
cudaStreamCreate(&computeStream);
}
inline void *acceleratorAllocDevice(size_t bytes)
{
void *ptr=NULL;
auto err = cudaMalloc((void **)&ptr,bytes);
if( err != cudaSuccess ) {
ptr = (void *) NULL;
printf(" cudaMalloc failed for %d %s \n",bytes,cudaGetErrorString(err));
}
return ptr;
};
inline void acceleratorFreeShared(void *ptr){ cudaFree(ptr);};
inline void acceleratorFreeDevice(void *ptr){ cudaFree(ptr);};
inline void acceleratorCopyToDevice(void *from,void *to,size_t bytes) { cudaMemcpy(to,from,bytes, cudaMemcpyHostToDevice);}
inline void acceleratorCopyFromDevice(void *from,void *to,size_t bytes){ cudaMemcpy(to,from,bytes, cudaMemcpyDeviceToHost);}
inline void acceleratorMemSet(void *base,int value,size_t bytes) { cudaMemset(base,value,bytes);}
#define accelerator_barrier(dummy) \
{ \
cudaStreamSynchronize(computeStream); \
cudaError err = cudaGetLastError(); \
if ( cudaSuccess != err ) { \
printf("accelerator_barrier(): Cuda error %s \n", \
cudaGetErrorString( err )); \
printf("File %s Line %d\n",__FILE__,__LINE__); \
fflush(stdout); \
if (acceleratorAbortOnGpuError) assert(err==cudaSuccess); \
} \
}
#endif
template<class T> void acceleratorPut(T& dev,T&host)
{
acceleratorCopyToDevice(&host,&dev,sizeof(T));
@ -55,9 +137,6 @@ template<class T> T acceleratorGet(T& dev)
acceleratorCopyFromDevice(&dev,&host,sizeof(T));
return host;
}
#define accelerator_barrier(dummy) { theAccelerator->wait(); }
#endif
/**************************************************************
* Allocator
@ -210,7 +289,270 @@ public:
gridblasHandle->wait();
#endif
}
/////////////////////////////////////////////////////////////
// Single matrix GEMM -- fp64 and fp32
/////////////////////////////////////////////////////////////
void gemm(GridBLASOperation_t OpA,
GridBLASOperation_t OpB,
int m,int n, int k,
ComplexD alpha,
ComplexD* Amk, // Device pointer
ComplexD* Bkn,
ComplexD beta,
ComplexD* Cmn)
{
RealD t2=usecond();
assert(OpA!=GridBLAS_OP_T); // Complex case expect no transpose
assert(OpB!=GridBLAS_OP_T);
int lda = m; // m x k column major
int ldb = k; // k x n column major
int ldc = m; // m x b column major
if(OpA!=GridBLAS_OP_N)
lda = k;
if(OpB!=GridBLAS_OP_N)
ldb = n;
static deviceVector<ComplexD> alpha_p(1);
static deviceVector<ComplexD> beta_p(1);
// can prestore the 1 and the zero on device
acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(ComplexD));
acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(ComplexD));
RealD t0=usecond();
#ifdef GRID_HIP
hipblasOperation_t hOpA;
hipblasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = HIPBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = HIPBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = HIPBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = HIPBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = HIPBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = HIPBLAS_OP_C;
auto err = hipblasZgemm(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(hipblasDoubleComplex *) &alpha_p[0],
(hipblasDoubleComplex *) Amk, lda,
(hipblasDoubleComplex *) Bkn, ldb,
(hipblasDoubleComplex *) &beta_p[0],
(hipblasDoubleComplex *) Cmn, ldc);
assert(err==HIPBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_CUDA
cublasOperation_t hOpA;
cublasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = CUBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = CUBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = CUBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = CUBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = CUBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = CUBLAS_OP_C;
auto err = cublasZgemm(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(cuDoubleComplex *) &alpha_p[0],
(cuDoubleComplex *) Amk, lda,
(cuDoubleComplex *) Bkn, ldb,
(cuDoubleComplex *) &beta_p[0],
(cuDoubleComplex *) Cmn, ldc);
assert(err==CUBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_SYCL
int64_t m64=m;
int64_t n64=n;
int64_t k64=k;
int64_t lda64=lda;
int64_t ldb64=ldb;
int64_t ldc64=ldc;
oneapi::mkl::transpose iOpA;
oneapi::mkl::transpose iOpB;
if ( OpA == GridBLAS_OP_N ) iOpA = oneapi::mkl::transpose::N;
if ( OpA == GridBLAS_OP_T ) iOpA = oneapi::mkl::transpose::T;
if ( OpA == GridBLAS_OP_C ) iOpA = oneapi::mkl::transpose::C;
if ( OpB == GridBLAS_OP_N ) iOpB = oneapi::mkl::transpose::N;
if ( OpB == GridBLAS_OP_T ) iOpB = oneapi::mkl::transpose::T;
if ( OpB == GridBLAS_OP_C ) iOpB = oneapi::mkl::transpose::C;
oneapi::mkl::blas::column_major::gemm(*gridblasHandle,
iOpA,
iOpB,
m64,n64,k64,
(ComplexD *) &alpha_p[0],
(const ComplexD *)Amk, (int64_t )lda64,
(const ComplexD *)Bkn, (int64_t )ldb64,
(ComplexD *) &beta_p[0],
(ComplexD *)Cmn, (int64_t)ldc64);
synchronise();
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
// Need a default/reference implementation; use Eigen
if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_N) ) {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk,m,k);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn,k,n);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn,m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_N) ) {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk,k,m);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn,k,n);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn,m,n);
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn ;
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_C) ) {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk,m,k);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn,n,k);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn,m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.adjoint() ;
} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_C) ) {
Eigen::Map<Eigen::MatrixXcd> eAmk(Amk,k,m);
Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn,n,k);
Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn,m,n);
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn.adjoint() ;
} else {
assert(0);
}
#endif
RealD t1=usecond();
RealD flops = 8.0*m*n*k;
RealD bytes = 1.0*sizeof(ComplexD)*(m*k+k*n+m*n);
}
void gemm(GridBLASOperation_t OpA,
GridBLASOperation_t OpB,
int m,int n, int k,
ComplexF alpha,
ComplexF* Amk, // Device pointer
ComplexF* Bkn,
ComplexF beta,
ComplexF* Cmn)
{
RealD t2=usecond();
assert(OpA!=GridBLAS_OP_T); // Complex case expect no transpose
assert(OpB!=GridBLAS_OP_T);
int lda = m; // m x k column major
int ldb = k; // k x n column major
int ldc = m; // m x b column major
if(OpA!=GridBLAS_OP_N)
lda = k;
if(OpB!=GridBLAS_OP_N)
ldb = n;
static deviceVector<ComplexF> alpha_p(1);
static deviceVector<ComplexF> beta_p(1);
// can prestore the 1 and the zero on device
acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(ComplexF));
acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(ComplexF));
RealD t0=usecond();
#ifdef GRID_HIP
hipblasOperation_t hOpA;
hipblasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = HIPBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = HIPBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = HIPBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = HIPBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = HIPBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = HIPBLAS_OP_C;
auto err = hipblasCgemm(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(hipblasComplex *) &alpha_p[0],
(hipblasComplex *) Amk, lda,
(hipblasComplex *) Bkn, ldb,
(hipblasComplex *) &beta_p[0],
(hipblasComplex *) Cmn, ldc);
assert(err==HIPBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_CUDA
cublasOperation_t hOpA;
cublasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = CUBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = CUBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = CUBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = CUBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = CUBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = CUBLAS_OP_C;
auto err = cublasCgemm(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(cuComplex *) &alpha_p[0],
(cuComplex *) Amk, lda,
(cuComplex *) Bkn, ldb,
(cuComplex *) &beta_p[0],
(cuComplex *) Cmn, ldc);
assert(err==CUBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_SYCL
int64_t m64=m;
int64_t n64=n;
int64_t k64=k;
int64_t lda64=lda;
int64_t ldb64=ldb;
int64_t ldc64=ldc;
oneapi::mkl::transpose iOpA;
oneapi::mkl::transpose iOpB;
if ( OpA == GridBLAS_OP_N ) iOpA = oneapi::mkl::transpose::N;
if ( OpA == GridBLAS_OP_T ) iOpA = oneapi::mkl::transpose::T;
if ( OpA == GridBLAS_OP_C ) iOpA = oneapi::mkl::transpose::C;
if ( OpB == GridBLAS_OP_N ) iOpB = oneapi::mkl::transpose::N;
if ( OpB == GridBLAS_OP_T ) iOpB = oneapi::mkl::transpose::T;
if ( OpB == GridBLAS_OP_C ) iOpB = oneapi::mkl::transpose::C;
oneapi::mkl::blas::column_major::gemm(*gridblasHandle,
iOpA,
iOpB,
m64,n64,k64,
(ComplexF *) &alpha_p[0],
(const ComplexF *)Amk, (int64_t )lda64,
(const ComplexF *)Bkn, (int64_t )ldb64,
(ComplexF *) &beta_p[0],
(ComplexF *)Cmn, (int64_t )ldc64);
synchronise();
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
// Need a default/reference implementation; use Eigen
if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_N) ) {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk,m,k);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn,k,n);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn,m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_N) ) {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk,k,m);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn,k,n);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn,m,n);
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn ;
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_C) ) {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk,m,k);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn,n,k);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn,m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.adjoint() ;
} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_C) ) {
Eigen::Map<Eigen::MatrixXcf> eAmk(Amk,k,m);
Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn,n,k);
Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn,m,n);
eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn.adjoint() ;
} else {
assert(0);
}
#endif
RealD t1=usecond();
RealD flops = 8.0*m*n*k;
RealD bytes = 1.0*sizeof(ComplexF)*(m*k+k*n+m*n);
}
/////////////////////////////////////////////////////////////
void gemmBatched(int m,int n, int k,
ComplexD alpha,
deviceVector<ComplexD*> &Amk, // pointer list to matrices
@ -241,36 +583,6 @@ public:
beta,
Cmn);
}
void gemmBatched(int m,int n, int k,
RealD alpha,
deviceVector<RealD*> &Amk, // pointer list to matrices
deviceVector<RealD*> &Bkn,
RealD beta,
deviceVector<RealD*> &Cmn)
{
gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
m,n,k,
alpha,
Amk,
Bkn,
beta,
Cmn);
}
void gemmBatched(int m,int n, int k,
RealF alpha,
deviceVector<RealF*> &Amk, // pointer list to matrices
deviceVector<RealF*> &Bkn,
RealF beta,
deviceVector<RealF*> &Cmn)
{
gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
m,n,k,
alpha,
Amk,
Bkn,
beta,
Cmn);
}
void gemmBatched(GridBLASOperation_t OpA,
GridBLASOperation_t OpB,
@ -623,301 +935,6 @@ public:
RealD flops = 8.0*m*n*k*batchCount;
RealD bytes = 1.0*sizeof(ComplexF)*(m*k+k*n+m*n)*batchCount;
}
///////////////////////////////////////////////////////////////////////////
// Single precision real GEMM
///////////////////////////////////////////////////////////////////////////
void gemmBatched(GridBLASOperation_t OpA,
GridBLASOperation_t OpB,
int m,int n, int k,
RealF alpha,
deviceVector<RealF*> &Amk, // pointer list to matrices
deviceVector<RealF*> &Bkn,
RealF beta,
deviceVector<RealF*> &Cmn)
{
RealD t2=usecond();
int32_t batchCount = Amk.size();
assert(OpA!=GridBLAS_OP_C); // Real case no conjugate
assert(OpB!=GridBLAS_OP_C);
int lda = m; // m x k column major
int ldb = k; // k x n column major
int ldc = m; // m x b column major
if(OpA!=GridBLAS_OP_N)
lda = k;
if(OpB!=GridBLAS_OP_N)
ldb = n;
static deviceVector<RealF> alpha_p(1);
static deviceVector<RealF> beta_p(1);
// can prestore the 1 and the zero on device
acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(RealF));
acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(RealF));
RealD t0=usecond();
assert(Bkn.size()==batchCount);
assert(Cmn.size()==batchCount);
#ifdef GRID_HIP
hipblasOperation_t hOpA;
hipblasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = HIPBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = HIPBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = HIPBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = HIPBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = HIPBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = HIPBLAS_OP_C;
auto err = hipblasSgemmBatched(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(float *) &alpha_p[0],
(float **)&Amk[0], lda,
(float **)&Bkn[0], ldb,
(float *) &beta_p[0],
(float **)&Cmn[0], ldc,
batchCount);
assert(err==HIPBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_CUDA
cublasOperation_t hOpA;
cublasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = CUBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = CUBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = CUBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = CUBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = CUBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = CUBLAS_OP_C;
auto err = cublasSgemmBatched(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(float *) &alpha_p[0],
(float **)&Amk[0], lda,
(float **)&Bkn[0], ldb,
(float *) &beta_p[0],
(float **)&Cmn[0], ldc,
batchCount);
assert(err==CUBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_SYCL
int64_t m64=m;
int64_t n64=n;
int64_t k64=k;
int64_t lda64=lda;
int64_t ldb64=ldb;
int64_t ldc64=ldc;
int64_t batchCount64=batchCount;
oneapi::mkl::transpose iOpA;
oneapi::mkl::transpose iOpB;
if ( OpA == GridBLAS_OP_N ) iOpA = oneapi::mkl::transpose::N;
if ( OpA == GridBLAS_OP_T ) iOpA = oneapi::mkl::transpose::T;
if ( OpA == GridBLAS_OP_C ) iOpA = oneapi::mkl::transpose::C;
if ( OpB == GridBLAS_OP_N ) iOpB = oneapi::mkl::transpose::N;
if ( OpB == GridBLAS_OP_T ) iOpB = oneapi::mkl::transpose::T;
if ( OpB == GridBLAS_OP_C ) iOpB = oneapi::mkl::transpose::C;
oneapi::mkl::blas::column_major::gemm_batch(*gridblasHandle,
&iOpA,
&iOpB,
&m64,&n64,&k64,
(float *) &alpha_p[0],
(const float **)&Amk[0], (const int64_t *)&lda64,
(const float **)&Bkn[0], (const int64_t *)&ldb64,
(float *) &beta_p[0],
(float **)&Cmn[0], (const int64_t *)&ldc64,
(int64_t)1,&batchCount64,std::vector<sycl::event>());
synchronise();
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
// Need a default/reference implementation; use Eigen
if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.transpose() ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn.transpose() ;
} );
} else {
assert(0);
}
#endif
RealD t1=usecond();
RealD flops = 2.0*m*n*k*batchCount;
RealD bytes = 1.0*sizeof(RealF)*(m*k+k*n+m*n)*batchCount;
}
///////////////////////////////////////////////////////////////////////////
// Double precision real GEMM
///////////////////////////////////////////////////////////////////////////
void gemmBatched(GridBLASOperation_t OpA,
GridBLASOperation_t OpB,
int m,int n, int k,
RealD alpha,
deviceVector<RealD*> &Amk, // pointer list to matrices
deviceVector<RealD*> &Bkn,
RealD beta,
deviceVector<RealD*> &Cmn)
{
RealD t2=usecond();
int32_t batchCount = Amk.size();
assert(OpA!=GridBLAS_OP_C); // Real case no conjugate
assert(OpB!=GridBLAS_OP_C);
int lda = m; // m x k column major
int ldb = k; // k x n column major
int ldc = m; // m x b column major
if(OpA!=GridBLAS_OP_N)
lda = k;
if(OpB!=GridBLAS_OP_N)
ldb = n;
static deviceVector<RealD> alpha_p(1);
static deviceVector<RealD> beta_p(1);
// can prestore the 1 and the zero on device
acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(RealD));
acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(RealD));
RealD t0=usecond();
assert(Bkn.size()==batchCount);
assert(Cmn.size()==batchCount);
#ifdef GRID_HIP
hipblasOperation_t hOpA;
hipblasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = HIPBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = HIPBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = HIPBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = HIPBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = HIPBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = HIPBLAS_OP_C;
auto err = hipblasDgemmBatched(gridblasHandle,
HIPBLAS_OP_N,
HIPBLAS_OP_N,
m,n,k,
(double *) &alpha_p[0],
(double **)&Amk[0], lda,
(double **)&Bkn[0], ldb,
(double *) &beta_p[0],
(double **)&Cmn[0], ldc,
batchCount);
assert(err==HIPBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_CUDA
cublasOperation_t hOpA;
cublasOperation_t hOpB;
if ( OpA == GridBLAS_OP_N ) hOpA = CUBLAS_OP_N;
if ( OpA == GridBLAS_OP_T ) hOpA = CUBLAS_OP_T;
if ( OpA == GridBLAS_OP_C ) hOpA = CUBLAS_OP_C;
if ( OpB == GridBLAS_OP_N ) hOpB = CUBLAS_OP_N;
if ( OpB == GridBLAS_OP_T ) hOpB = CUBLAS_OP_T;
if ( OpB == GridBLAS_OP_C ) hOpB = CUBLAS_OP_C;
auto err = cublasDgemmBatched(gridblasHandle,
hOpA,
hOpB,
m,n,k,
(double *) &alpha_p[0],
(double **)&Amk[0], lda,
(double **)&Bkn[0], ldb,
(double *) &beta_p[0],
(double **)&Cmn[0], ldc,
batchCount);
assert(err==CUBLAS_STATUS_SUCCESS);
#endif
#ifdef GRID_SYCL
int64_t m64=m;
int64_t n64=n;
int64_t k64=k;
int64_t lda64=lda;
int64_t ldb64=ldb;
int64_t ldc64=ldc;
int64_t batchCount64=batchCount;
oneapi::mkl::transpose iOpA;
oneapi::mkl::transpose iOpB;
if ( OpA == GridBLAS_OP_N ) iOpA = oneapi::mkl::transpose::N;
if ( OpA == GridBLAS_OP_T ) iOpA = oneapi::mkl::transpose::T;
if ( OpA == GridBLAS_OP_C ) iOpA = oneapi::mkl::transpose::C;
if ( OpB == GridBLAS_OP_N ) iOpB = oneapi::mkl::transpose::N;
if ( OpB == GridBLAS_OP_T ) iOpB = oneapi::mkl::transpose::T;
if ( OpB == GridBLAS_OP_C ) iOpB = oneapi::mkl::transpose::C;
oneapi::mkl::blas::column_major::gemm_batch(*gridblasHandle,
&iOpA,
&iOpB,
&m64,&n64,&k64,
(double *) &alpha_p[0],
(const double **)&Amk[0], (const int64_t *)&lda64,
(const double **)&Bkn[0], (const int64_t *)&ldb64,
(double *) &beta_p[0],
(double **)&Cmn[0], (const int64_t *)&ldc64,
(int64_t)1,&batchCount64,std::vector<sycl::event>());
synchronise();
#endif
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
// Need a default/reference implementation; use Eigen
if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_N) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],k,n);
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn ;
});
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],m,k);
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk * eBkn.transpose() ;
});
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_T) ) {
thread_for (p, batchCount, {
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],k,m);
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],n,k);
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn.transpose() ;
});
} else {
assert(0);
}
#endif
RealD t1=usecond();
RealD flops = 2.0*m*n*k*batchCount;
RealD bytes = 1.0*sizeof(RealD)*(m*k+k*n+m*n)*batchCount;
}
template<class CComplex>
double benchmark(int M, int N, int K, int BATCH)
@ -967,6 +984,47 @@ public:
return flops; // Returns gigaflops
}
template<class CComplex>
double benchmark(int M, int N, int K)
{
int32_t N_A = M*K;
int32_t N_B = K*N;
int32_t N_C = M*N;
deviceVector<CComplex> A(N_A); acceleratorMemSet(&A[0],0,N_A*sizeof(CComplex));
deviceVector<CComplex> B(N_B); acceleratorMemSet(&B[0],0,N_B*sizeof(CComplex));
deviceVector<CComplex> C(N_C); acceleratorMemSet(&C[0],0,N_C*sizeof(CComplex));
CComplex alpha(1.0);
CComplex beta (1.0);
RealD flops = 8.0*M*N*K;
int ncall=10;
gemm(GridBLAS_OP_C,GridBLAS_OP_N,
M,N,K,
alpha,
&A[0], // m x k
&B[0], // k x n
beta,
&C[0]);
synchronise();
RealD t0 = usecond();
for(int i=0;i<ncall;i++){
gemm(GridBLAS_OP_N,GridBLAS_OP_N,
M,N,K,
alpha,
&A[0], // m x k
&B[0], // k x n
beta,
&C[0]);
synchronise();
}
RealD t1 = usecond();
RealD bytes = 1.0*sizeof(CComplex)*(M*N*2+N*K+M*K);
flops = 8.0*M*N*K*ncall;
flops = flops/(t1-t0)/1.e3;
return flops; // Returns gigaflops
}
};
@ -1035,6 +1093,21 @@ static void BLAS(void)
std::cout<< M<<"\t\t"<<N<<"\t\t"<<K<<"\t\t"<<BATCH<<"\t\t"<<p<<std::endl;
}}
fprintf(FP,"\n\n\n");
std::cout << "----------------------------------------------------------"<<std::endl;
std::cout << " M "<<"\t\t"<<"N"<<"\t\t\t"<<"K"<<"\t\t"<<"Gflop/s / rank (inner product matrix)"<<std::endl;
std::cout << "----------------------------------------------------------"<<std::endl;
{
int M=12;
int N=12;
std::vector<int> ks({4*1024*1024, 2*1024*1024, 1024*1024, 256*1024, 1024 });
for( int kk=0;kk<ks.size();kk++ ) {
int K = ks[kk];
double p=blas.benchmark<CComplex>(M,N,K);
fprintf(FP,"%d, %d, %d, %d, %f\n", M, N, K, 1, p);
std::cout<< M<<"\t\t"<<N<<"\t\t"<<K<<"\t\t"<<1<<"\t\t"<<p<<std::endl;
}
}
std::cout << "=================================================================================="<<std::endl;
};

View File

@ -1,2 +1,2 @@
mpicxx -qmkl=parallel -fsycl BatchBlasBench.cc -o BatchBlasBench
mpicxx -qmkl=parallel -fsycl BatchBlasBench.cc -o BatchBlasBench -DGRID_SYCL

View File

@ -0,0 +1,5 @@
CXX=hipcc
MPICXX=mpicxx
CXXFLAGS="-fPIC -I{$ROCM_PATH}/include/ -I${MPICH_DIR}/include -L/lib64 -I/opt/cray/pe/mpich/8.1.28/ofi/gnu/12.3/include -DGRID_HIP"
LDFLAGS="-L/lib64 -L${MPICH_DIR}/lib -lmpi -L${CRAY_MPICH_ROOTDIR}/gtl/lib -lmpi_gtl_hsa -lamdhip64 -lhipblas -lrocblas -lmpi_gnu_123"
hipcc $CXXFLAGS $LDFLAGS BatchBlasBench.cc -o BatchBlasBench

View File

@ -0,0 +1,2 @@
mpicxx -qmkl=parallel -fsycl BatchBlasBench.cc -o BatchBlasBench -DGRID_SYCL

View File

@ -50,6 +50,7 @@ NAMESPACE_CHECK(approx);
#include <Grid/algorithms/deflation/Deflation.h>
#include <Grid/algorithms/deflation/MultiRHSBlockProject.h>
#include <Grid/algorithms/deflation/MultiRHSDeflation.h>
#include <Grid/algorithms/deflation/MultiRHSBlockCGLinalg.h>
NAMESPACE_CHECK(deflation);
#include <Grid/algorithms/iterative/ConjugateGradient.h>
NAMESPACE_CHECK(ConjGrad);

View File

@ -103,6 +103,38 @@ public:
_Mat.MdagM(in,out);
}
};
template<class Matrix,class Field>
class MMdagLinearOperator : public LinearOperatorBase<Field> {
Matrix &_Mat;
public:
MMdagLinearOperator(Matrix &Mat): _Mat(Mat){};
// Support for coarsening to a multigrid
void OpDiag (const Field &in, Field &out) {
_Mat.Mdiag(in,out);
}
void OpDir (const Field &in, Field &out,int dir,int disp) {
_Mat.Mdir(in,out,dir,disp);
}
void OpDirAll (const Field &in, std::vector<Field> &out){
_Mat.MdirAll(in,out);
};
void Op (const Field &in, Field &out){
_Mat.M(in,out);
}
void AdjOp (const Field &in, Field &out){
_Mat.Mdag(in,out);
}
void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){
_Mat.MMdag(in,out);
ComplexD dot = innerProduct(in,out);
n1=real(dot);
n2=norm2(out);
}
void HermOp(const Field &in, Field &out){
_Mat.MMdag(in,out);
}
};
////////////////////////////////////////////////////////////////////
// Construct herm op and shift it for mgrid smoother

View File

@ -45,6 +45,11 @@ public:
M(in,tmp);
Mdag(tmp,out);
}
virtual void MMdag(const Field &in, Field &out) {
Field tmp (in.Grid());
Mdag(in,tmp);
M(tmp,out);
}
virtual void Mdiag (const Field &in, Field &out)=0;
virtual void Mdir (const Field &in, Field &out,int dir, int disp)=0;
virtual void MdirAll (const Field &in, std::vector<Field> &out)=0;

View File

@ -59,7 +59,7 @@ public:
RealD diff = hi-lo;
RealD delta = diff*1.0e-9;
for (RealD x=lo; x<hi; x+=delta) {
delta*=1.1;
delta*=1.02;
RealD f = approx(x);
out<< x<<" "<<f<<std::endl;
}
@ -131,6 +131,26 @@ public:
Coeffs[j] = s * 2.0/order;
}
};
template<class functor>
void Init(RealD _lo,RealD _hi,int _order, functor & func)
{
lo=_lo;
hi=_hi;
order=_order;
if(order < 2) exit(-1);
Coeffs.resize(order);
for(int j=0;j<order;j++){
RealD s=0;
for(int k=0;k<order;k++){
RealD y=std::cos(M_PI*(k+0.5)/order);
RealD x=0.5*(y*(hi-lo)+(hi+lo));
RealD f=func(x);
s=s+f*std::cos( j*M_PI*(k+0.5)/order );
}
Coeffs[j] = s * 2.0/order;
}
};
void JacksonSmooth(void){

View File

@ -0,0 +1,376 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: MultiRHSBlockCGLinalg.h
Copyright (C) 2024
Author: Peter Boyle <pboyle@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
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
NAMESPACE_BEGIN(Grid);
/* Need helper object for BLAS accelerated mrhs blockCG */
template<class Field>
class MultiRHSBlockCGLinalg
{
public:
typedef typename Field::scalar_type scalar;
typedef typename Field::scalar_object scalar_object;
typedef typename Field::vector_object vector_object;
deviceVector<scalar> BLAS_X; // nrhs x vol -- the sources
deviceVector<scalar> BLAS_Y; // nrhs x vol -- the result
deviceVector<scalar> BLAS_C; // nrhs x nrhs -- the coefficients
deviceVector<scalar> BLAS_Cred; // nrhs x nrhs x oSites -- reduction buffer
deviceVector<scalar *> Xdip;
deviceVector<scalar *> Ydip;
deviceVector<scalar *> Cdip;
MultiRHSBlockCGLinalg() {};
~MultiRHSBlockCGLinalg(){ Deallocate(); };
void Deallocate(void)
{
Xdip.resize(0);
Ydip.resize(0);
Cdip.resize(0);
BLAS_Cred.resize(0);
BLAS_C.resize(0);
BLAS_X.resize(0);
BLAS_Y.resize(0);
}
void MaddMatrix(std::vector<Field> &AP, Eigen::MatrixXcd &m , const std::vector<Field> &X,const std::vector<Field> &Y,RealD scale=1.0)
{
std::vector<Field> Y_copy(AP.size(),AP[0].Grid());
for(int r=0;r<AP.size();r++){
Y_copy[r] = Y[r];
}
MulMatrix(AP,m,X);
for(int r=0;r<AP.size();r++){
AP[r] = scale*AP[r]+Y_copy[r];
}
}
void MulMatrix(std::vector<Field> &Y, Eigen::MatrixXcd &m , const std::vector<Field> &X)
{
typedef typename Field::scalar_type scomplex;
GridBase *grid;
uint64_t vol;
uint64_t words;
int nrhs = Y.size();
grid = X[0].Grid();
vol = grid->lSites();
words = sizeof(scalar_object)/sizeof(scalar);
int64_t vw = vol * words;
RealD t0 = usecond();
BLAS_X.resize(nrhs * vw); // cost free if size doesn't change
BLAS_Y.resize(nrhs * vw); // cost free if size doesn't change
BLAS_C.resize(nrhs * nrhs);// cost free if size doesn't change
RealD t1 = usecond();
/////////////////////////////////////////////
// Copy in the multi-rhs sources
/////////////////////////////////////////////
for(int r=0;r<nrhs;r++){
int64_t offset = r*vw;
autoView(x_v,X[r],AcceleratorRead);
acceleratorCopyDeviceToDevice(&x_v[0],&BLAS_X[offset],sizeof(scalar_object)*vol);
}
// Assumes Eigen storage contiguous
acceleratorCopyToDevice(&m(0,0),&BLAS_C[0],BLAS_C.size()*sizeof(scalar));
/*
* in Fortran column major notation (cuBlas order)
*
* Xxr = [X1(x)][..][Xn(x)]
* Yxr = [Y1(x)][..][Ym(x)]
* Y = X . C
*/
deviceVector<scalar *> Xd(1);
deviceVector<scalar *> Yd(1);
deviceVector<scalar *> Cd(1);
scalar * Xh = & BLAS_X[0];
scalar * Yh = & BLAS_Y[0];
scalar * Ch = & BLAS_C[0];
acceleratorPut(Xd[0],Xh);
acceleratorPut(Yd[0],Yh);
acceleratorPut(Cd[0],Ch);
RealD t2 = usecond();
GridBLAS BLAS;
/////////////////////////////////////////
// Y = X*C (transpose?)
/////////////////////////////////////////
BLAS.gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
vw,nrhs,nrhs,
scalar(1.0),
Xd,
Cd,
scalar(0.0), // wipe out Y
Yd);
BLAS.synchronise();
RealD t3 = usecond();
// Copy back Y = m X
for(int r=0;r<nrhs;r++){
int64_t offset = r*vw;
autoView(y_v,Y[r],AcceleratorWrite);
acceleratorCopyDeviceToDevice(&BLAS_Y[offset],&y_v[0],sizeof(scalar_object)*vol);
}
RealD t4 = usecond();
std::cout << "MulMatrix alloc took "<< t1-t0<<" us"<<std::endl;
std::cout << "MulMatrix preamble took "<< t2-t1<<" us"<<std::endl;
std::cout << "MulMatrix blas took "<< t3-t2<<" us"<<std::endl;
std::cout << "MulMatrix copy took "<< t4-t3<<" us"<<std::endl;
std::cout << "MulMatrix total "<< t4-t0<<" us"<<std::endl;
}
void InnerProductMatrix(Eigen::MatrixXcd &m , const std::vector<Field> &X, const std::vector<Field> &Y)
{
#if 0
int nrhs;
GridBase *grid;
uint64_t vol;
uint64_t words;
nrhs = X.size();
assert(X.size()==Y.size());
conformable(X[0],Y[0]);
grid = X[0].Grid();
vol = grid->lSites();
words = sizeof(scalar_object)/sizeof(scalar);
int64_t vw = vol * words;
RealD t0 = usecond();
BLAS_X.resize(nrhs * vw); // cost free if size doesn't change
BLAS_Y.resize(nrhs * vw); // cost free if size doesn't change
BLAS_C.resize(nrhs * nrhs);// cost free if size doesn't change
RealD t1 = usecond();
/////////////////////////////////////////////
// Copy in the multi-rhs sources
/////////////////////////////////////////////
for(int r=0;r<nrhs;r++){
int64_t offset = r*vw;
autoView(x_v,X[r],AcceleratorRead);
acceleratorCopyDeviceToDevice(&x_v[0],&BLAS_X[offset],sizeof(scalar_object)*vol);
autoView(y_v,Y[r],AcceleratorRead);
acceleratorCopyDeviceToDevice(&y_v[0],&BLAS_Y[offset],sizeof(scalar_object)*vol);
}
RealD t2 = usecond();
/*
* in Fortran column major notation (cuBlas order)
*
* Xxr = [X1(x)][..][Xn(x)]
*
* Yxr = [Y1(x)][..][Ym(x)]
*
* C_rs = X^dag Y
*/
deviceVector<scalar *> Xd(1);
deviceVector<scalar *> Yd(1);
deviceVector<scalar *> Cd(1);
scalar * Xh = & BLAS_X[0];
scalar * Yh = & BLAS_Y[0];
scalar * Ch = & BLAS_C[0];
acceleratorPut(Xd[0],Xh);
acceleratorPut(Yd[0],Yh);
acceleratorPut(Cd[0],Ch);
GridBLAS BLAS;
RealD t3 = usecond();
/////////////////////////////////////////
// C_rs = X^dag Y
/////////////////////////////////////////
BLAS.gemmBatched(GridBLAS_OP_C,GridBLAS_OP_N,
nrhs,nrhs,vw,
ComplexD(1.0),
Xd,
Yd,
ComplexD(0.0), // wipe out C
Cd);
BLAS.synchronise();
RealD t4 = usecond();
std::vector<scalar> HOST_C(BLAS_C.size()); // nrhs . nrhs -- the coefficients
acceleratorCopyFromDevice(&BLAS_C[0],&HOST_C[0],BLAS_C.size()*sizeof(scalar));
grid->GlobalSumVector(&HOST_C[0],nrhs*nrhs);
RealD t5 = usecond();
for(int rr=0;rr<nrhs;rr++){
for(int r=0;r<nrhs;r++){
int off = r+nrhs*rr;
m(r,rr)=HOST_C[off];
}
}
RealD t6 = usecond();
uint64_t M=nrhs;
uint64_t N=nrhs;
uint64_t K=vw;
RealD bytes = 1.0*sizeof(ComplexD)*(M*N*2+N*K+M*K);
RealD flops = 8.0*M*N*K;
flops = flops/(t4-t3)/1.e3;
bytes = bytes/(t4-t3)/1.e3;
std::cout << "InnerProductMatrix m,n,k "<< M<<","<<N<<","<<K<<std::endl;
std::cout << "InnerProductMatrix alloc t1 "<< t1-t0<<" us"<<std::endl;
std::cout << "InnerProductMatrix cp t2 "<< t2-t1<<" us"<<std::endl;
std::cout << "InnerProductMatrix setup t3 "<< t3-t2<<" us"<<std::endl;
std::cout << "InnerProductMatrix blas t4 "<< t4-t3<<" us"<<std::endl;
std::cout << "InnerProductMatrix blas "<< flops<<" GF/s"<<std::endl;
std::cout << "InnerProductMatrix blas "<< bytes<<" GB/s"<<std::endl;
std::cout << "InnerProductMatrix gsum t5 "<< t5-t4<<" us"<<std::endl;
std::cout << "InnerProductMatrix cp t6 "<< t6-t5<<" us"<<std::endl;
std::cout << "InnerProductMatrix took "<< t6-t0<<" us"<<std::endl;
#else
int nrhs;
GridBase *grid;
uint64_t vol;
uint64_t words;
nrhs = X.size();
assert(X.size()==Y.size());
conformable(X[0],Y[0]);
grid = X[0].Grid();
int rd0 = grid->_rdimensions[0] * grid->_rdimensions[1];
vol = grid->oSites()/rd0;
words = rd0*sizeof(vector_object)/sizeof(scalar);
int64_t vw = vol * words;
assert(vw == grid->lSites()*sizeof(scalar_object)/sizeof(scalar));
RealD t0 = usecond();
BLAS_X.resize(nrhs * vw); // cost free if size doesn't change
BLAS_Y.resize(nrhs * vw); // cost free if size doesn't change
BLAS_Cred.resize(nrhs * nrhs * vol);// cost free if size doesn't change
RealD t1 = usecond();
/////////////////////////////////////////////
// Copy in the multi-rhs sources -- layout batched BLAS ready
/////////////////////////////////////////////
for(int r=0;r<nrhs;r++){
autoView(x_v,X[r],AcceleratorRead);
autoView(y_v,Y[r],AcceleratorRead);
scalar *from_x=(scalar *)&x_v[0];
scalar *from_y=(scalar *)&y_v[0];
scalar *BX = &BLAS_X[0];
scalar *BY = &BLAS_Y[0];
accelerator_for(ssw,vw,1,{
uint64_t ss=ssw/words;
uint64_t w=ssw%words;
uint64_t offset = w+r*words+ss*nrhs*words; // [ss][rhs][words]
BX[offset] = from_x[ssw];
BY[offset] = from_y[ssw];
});
}
RealD t2 = usecond();
/*
* in Fortran column major notation (cuBlas order)
*
* Xxr = [X1(x)][..][Xn(x)]
*
* Yxr = [Y1(x)][..][Ym(x)]
*
* C_rs = X^dag Y
*/
Xdip.resize(vol);
Ydip.resize(vol);
Cdip.resize(vol);
std::vector<scalar *> Xh(vol);
std::vector<scalar *> Yh(vol);
std::vector<scalar *> Ch(vol);
for(uint64_t ss=0;ss<vol;ss++){
Xh[ss] = & BLAS_X[ss*nrhs*words];
Yh[ss] = & BLAS_Y[ss*nrhs*words];
Ch[ss] = & BLAS_Cred[ss*nrhs*nrhs];
}
acceleratorCopyToDevice(&Xh[0],&Xdip[0],vol*sizeof(scalar *));
acceleratorCopyToDevice(&Yh[0],&Ydip[0],vol*sizeof(scalar *));
acceleratorCopyToDevice(&Ch[0],&Cdip[0],vol*sizeof(scalar *));
GridBLAS BLAS;
RealD t3 = usecond();
/////////////////////////////////////////
// C_rs = X^dag Y
/////////////////////////////////////////
BLAS.gemmBatched(GridBLAS_OP_C,GridBLAS_OP_N,
nrhs,nrhs,words,
ComplexD(1.0),
Xdip,
Ydip,
ComplexD(0.0), // wipe out C
Cdip);
BLAS.synchronise();
RealD t4 = usecond();
std::vector<scalar> HOST_C(BLAS_Cred.size()); // nrhs . nrhs -- the coefficients
acceleratorCopyFromDevice(&BLAS_Cred[0],&HOST_C[0],BLAS_Cred.size()*sizeof(scalar));
RealD t5 = usecond();
m = Eigen::MatrixXcd::Zero(nrhs,nrhs);
for(int ss=0;ss<vol;ss++){
Eigen::Map<Eigen::MatrixXcd> eC((std::complex<double> *)&HOST_C[ss*nrhs*nrhs],nrhs,nrhs);
m = m + eC;
}
RealD t6l = usecond();
grid->GlobalSumVector((scalar *) &m(0,0),nrhs*nrhs);
RealD t6 = usecond();
uint64_t M=nrhs;
uint64_t N=nrhs;
uint64_t K=vw;
RealD xybytes = grid->lSites()*sizeof(scalar_object);
RealD bytes = 1.0*sizeof(ComplexD)*(M*N*2+N*K+M*K);
RealD flops = 8.0*M*N*K;
flops = flops/(t4-t3)/1.e3;
bytes = bytes/(t4-t3)/1.e3;
xybytes = 4*xybytes/(t2-t1)/1.e3;
std::cout << "InnerProductMatrix m,n,k "<< M<<","<<N<<","<<K<<std::endl;
std::cout << "InnerProductMatrix alloc t1 "<< t1-t0<<" us"<<std::endl;
std::cout << "InnerProductMatrix cp t2 "<< t2-t1<<" us "<<xybytes<<" GB/s"<<std::endl;
std::cout << "InnerProductMatrix setup t3 "<< t3-t2<<" us"<<std::endl;
std::cout << "InnerProductMatrix blas t4 "<< t4-t3<<" us"<<std::endl;
std::cout << "InnerProductMatrix blas "<< flops<<" GF/s"<<std::endl;
std::cout << "InnerProductMatrix blas "<< bytes<<" GB/s"<<std::endl;
std::cout << "InnerProductMatrix cp t5 "<< t5-t4<<" us"<<std::endl;
std::cout << "InnerProductMatrix lsum t6l "<< t6l-t5<<" us"<<std::endl;
std::cout << "InnerProductMatrix gsum t6 "<< t6-t6l<<" us"<<std::endl;
std::cout << "InnerProductMatrix took "<< t6-t0<<" us"<<std::endl;
#endif
}
};
NAMESPACE_END(Grid);

View File

@ -447,10 +447,10 @@ public:
/////////////////////////////////////////
BLAS.gemmBatched(GridBLAS_OP_C,GridBLAS_OP_N,
nbasis,nrhs,vw,
ComplexD(1.0),
scalar(1.0),
Vd,
Fd,
ComplexD(0.0), // wipe out C
scalar(0.0), // wipe out C
Cd);
BLAS.synchronise();
// std::cout << "BlockProject done"<<std::endl;
@ -497,10 +497,10 @@ public:
int64_t vw = block_vol * words;
BLAS.gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
vw,nrhs,nbasis,
ComplexD(1.0),
scalar(1.0),
Vd,
Cd,
ComplexD(0.0), // wipe out C
scalar(0.0), // wipe out C
Fd);
BLAS.synchronise();
// std::cout << " blas call done"<<std::endl;

View File

@ -182,10 +182,10 @@ public:
/////////////////////////////////////////
BLAS.gemmBatched(GridBLAS_OP_C,GridBLAS_OP_N,
nev,nrhs,vw,
ComplexD(1.0),
scalar(1.0),
Ed,
Rd,
ComplexD(0.0), // wipe out C
scalar(0.0), // wipe out C
Cd);
BLAS.synchronise();
@ -210,10 +210,10 @@ public:
/////////////////////////////////////////
BLAS.gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
vw,nrhs,nev,
ComplexD(1.0),
scalar(1.0),
Ed, // x . nev
Cd, // nev . nrhs
ComplexD(0.0),
scalar(0.0),
Gd);
BLAS.synchronise();

View File

@ -53,6 +53,7 @@ class TwoLevelCGmrhs
// Fine operator, Smoother, CoarseSolver
LinearOperatorBase<Field> &_FineLinop;
LinearFunction<Field> &_Smoother;
MultiRHSBlockCGLinalg<Field> _BlockCGLinalg;
GridStopWatch ProjectTimer;
GridStopWatch PromoteTimer;
@ -79,6 +80,301 @@ class TwoLevelCGmrhs
// Vector case
virtual void operator() (std::vector<Field> &src, std::vector<Field> &x)
{
SolveSingleSystem(src,x);
// SolvePrecBlockCG(src,x);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
// Thin QR factorisation (google it)
////////////////////////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
//Dimensions
// R_{ferm x Nblock} = Q_{ferm x Nblock} x C_{Nblock x Nblock} -> ferm x Nblock
//
// Rdag R = m_rr = Herm = L L^dag <-- Cholesky decomposition (LLT routine in Eigen)
//
// Q C = R => Q = R C^{-1}
//
// Want Ident = Q^dag Q = C^{-dag} R^dag R C^{-1} = C^{-dag} L L^dag C^{-1} = 1_{Nblock x Nblock}
//
// Set C = L^{dag}, and then Q^dag Q = ident
//
// Checks:
// Cdag C = Rdag R ; passes.
// QdagQ = 1 ; passes
////////////////////////////////////////////////////////////////////////////////////////////////////
void ThinQRfact (Eigen::MatrixXcd &m_zz,
Eigen::MatrixXcd &C,
Eigen::MatrixXcd &Cinv,
std::vector<Field> & Q,
std::vector<Field> & MQ,
const std::vector<Field> & Z,
const std::vector<Field> & MZ)
{
RealD t0=usecond();
_BlockCGLinalg.InnerProductMatrix(m_zz,MZ,Z);
RealD t1=usecond();
m_zz = 0.5*(m_zz+m_zz.adjoint());
Eigen::MatrixXcd L = m_zz.llt().matrixL();
C = L.adjoint();
Cinv = C.inverse();
RealD t3=usecond();
_BlockCGLinalg.MulMatrix( Q,Cinv,Z);
_BlockCGLinalg.MulMatrix(MQ,Cinv,MZ);
RealD t4=usecond();
std::cout << " ThinQRfact IP :"<< t1-t0<<" us"<<std::endl;
std::cout << " ThinQRfact Eigen :"<< t3-t1<<" us"<<std::endl;
std::cout << " ThinQRfact MulMat:"<< t4-t3<<" us"<<std::endl;
}
virtual void SolvePrecBlockCG (std::vector<Field> &src, std::vector<Field> &X)
{
std::cout << GridLogMessage<<"HDCG: mrhs fPrecBlockcg starting"<<std::endl;
src[0].Grid()->Barrier();
int nrhs = src.size();
// std::vector<RealD> f(nrhs);
// std::vector<RealD> rtzp(nrhs);
// std::vector<RealD> rtz(nrhs);
// std::vector<RealD> a(nrhs);
// std::vector<RealD> d(nrhs);
// std::vector<RealD> b(nrhs);
// std::vector<RealD> rptzp(nrhs);
////////////////////////////////////////////
//Initial residual computation & set up
////////////////////////////////////////////
std::vector<RealD> ssq(nrhs);
for(int rhs=0;rhs<nrhs;rhs++){
ssq[rhs]=norm2(src[rhs]); assert(ssq[rhs]!=0.0);
}
///////////////////////////
// Fields -- eliminate duplicates between fPcg and block cg
///////////////////////////
std::vector<Field> Mtmp(nrhs,grid);
std::vector<Field> tmp(nrhs,grid);
std::vector<Field> Z(nrhs,grid); // Rename Z to R
std::vector<Field> MZ(nrhs,grid); // Rename MZ to Z
std::vector<Field> Q(nrhs,grid); //
std::vector<Field> MQ(nrhs,grid); // Rename to P
std::vector<Field> D(nrhs,grid);
std::vector<Field> AD(nrhs,grid);
/************************************************************************
* Preconditioned Block conjugate gradient rQ
* Generalise Sebastien Birk Thesis, after Dubrulle 2001.
* Introduce preconditioning following Saad Ch9
************************************************************************
* Dimensions:
*
* X,B etc... ==(Nferm x nrhs)
* Matrix A==(Nferm x Nferm)
*
* Nferm = Nspin x Ncolour x Ncomplex x Nlattice_site
* QC => Thin QR factorisation (google it)
*
* R = B-AX
* Z = Mi R
* QC = Z
* D = Q
* for k:
* R = AD
* Z = Mi R
* M = [D^dag R]^{-1}
* X = X + D M C
* QS = Q - Z.M
* D = Q + D S^dag
* C = S C
*/
Eigen::MatrixXcd m_DZ = Eigen::MatrixXcd::Identity(nrhs,nrhs);
Eigen::MatrixXcd m_M = Eigen::MatrixXcd::Identity(nrhs,nrhs);
Eigen::MatrixXcd m_zz = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_rr = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_C = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_Cinv = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_S = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_Sinv = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_tmp = Eigen::MatrixXcd::Identity(nrhs,nrhs);
Eigen::MatrixXcd m_tmp1 = Eigen::MatrixXcd::Identity(nrhs,nrhs);
GridStopWatch HDCGTimer;
//////////////////////////
// x0 = Vstart -- possibly modify guess
//////////////////////////
Vstart(X,src);
//////////////////////////
// R = B-AX
//////////////////////////
for(int rhs=0;rhs<nrhs;rhs++){
// r0 = b -A x0
_FineLinop.HermOp(X[rhs],tmp[rhs]);
axpy (Z[rhs], -1.0,tmp[rhs], src[rhs]); // Computes R=Z=src - A X0
}
//////////////////////////////////
// Compute MZ = M1 Z = M1 B - M1 A x0
//////////////////////////////////
PcgM1(Z,MZ);
//////////////////////////////////
// QC = Z
//////////////////////////////////
ThinQRfact (m_zz, m_C, m_Cinv, Q, MQ, Z, MZ);
//////////////////////////////////
// D=MQ
//////////////////////////////////
for(int b=0;b<nrhs;b++) D[b]=MQ[b]; // LLT rotation of the MZ basis of search dirs
std::cout << GridLogMessage<<"PrecBlockCGrQ vec computed initial residual and QR fact " <<std::endl;
ProjectTimer.Reset();
PromoteTimer.Reset();
DeflateTimer.Reset();
CoarseTimer.Reset();
SmoothTimer.Reset();
FineTimer.Reset();
InsertTimer.Reset();
GridStopWatch M1Timer;
GridStopWatch M2Timer;
GridStopWatch M3Timer;
GridStopWatch LinalgTimer;
GridStopWatch InnerProdTimer;
HDCGTimer.Start();
std::vector<RealD> rn(nrhs);
for (int k=0;k<=MaxIterations;k++){
////////////////////
// Z = AD
////////////////////
M3Timer.Start();
for(int b=0;b<nrhs;b++) _FineLinop.HermOp(D[b], Z[b]);
M3Timer.Stop();
////////////////////
// MZ = M1 Z <==== the Multigrid preconditioner
////////////////////
M1Timer.Start();
PcgM1(Z,MZ);
M1Timer.Stop();
FineTimer.Start();
////////////////////
// M = [D^dag Z]^{-1} = (<Ddag MZ>_M)^{-1} inner prod, generalising Saad derivation of Precon CG
////////////////////
InnerProdTimer.Start();
_BlockCGLinalg.InnerProductMatrix(m_DZ,D,Z);
InnerProdTimer.Stop();
m_M = m_DZ.inverse();
///////////////////////////
// X = X + D MC
///////////////////////////
m_tmp = m_M * m_C;
LinalgTimer.Start();
_BlockCGLinalg.MaddMatrix(X,m_tmp, D,X); // D are the search directions and X takes the updates
LinalgTimer.Stop();
///////////////////////////
// QS = Q - M Z
// (MQ) S = MQ - M (M1Z)
///////////////////////////
LinalgTimer.Start();
_BlockCGLinalg.MaddMatrix(tmp ,m_M, Z, Q,-1.0);
_BlockCGLinalg.MaddMatrix(Mtmp,m_M,MZ,MQ,-1.0);
ThinQRfact (m_zz, m_S, m_Sinv, Q, MQ, tmp, Mtmp);
LinalgTimer.Stop();
////////////////////////////
// D = MQ + D S^dag
////////////////////////////
m_tmp = m_S.adjoint();
LinalgTimer.Start();
_BlockCGLinalg.MaddMatrix(D,m_tmp,D,MQ);
LinalgTimer.Stop();
////////////////////////////
// C = S C
////////////////////////////
m_C = m_S*m_C;
////////////////////////////
// convergence monitor
////////////////////////////
m_rr = m_C.adjoint() * m_C;
FineTimer.Stop();
RealD max_resid=0;
RealD rrsum=0;
RealD sssum=0;
RealD rr;
for(int b=0;b<nrhs;b++) {
rrsum+=real(m_rr(b,b));
sssum+=ssq[b];
rr = real(m_rr(b,b))/ssq[b];
if ( rr > max_resid ) max_resid = rr;
}
std::cout << GridLogMessage <<
"\t Prec BlockCGrQ Iteration "<<k<<" ave resid "<< std::sqrt(rrsum/sssum) << " max "<< std::sqrt(max_resid) <<std::endl;
if ( max_resid < Tolerance*Tolerance ) {
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ converged in "<<k<<" iterations and "<<HDCGTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Linalg "<<LinalgTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : fine H "<<M3Timer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : prec M1 "<<M1Timer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"**** M1 breakdown:"<<std::endl;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Project "<<ProjectTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Promote "<<PromoteTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Deflate "<<DeflateTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Coarse "<<CoarseTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Fine "<<FineTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Smooth "<<SmoothTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Insert "<<InsertTimer.Elapsed()<<std::endl;;
for(int rhs=0;rhs<nrhs;rhs++){
_FineLinop.HermOp(X[rhs],tmp[rhs]);
Field mytmp(grid);
axpy(mytmp,-1.0,src[rhs],tmp[rhs]);
RealD xnorm = sqrt(norm2(X[rhs]));
RealD srcnorm = sqrt(norm2(src[rhs]));
RealD tmpnorm = sqrt(norm2(mytmp));
RealD true_residual = tmpnorm/srcnorm;
std::cout<<GridLogMessage
<<"HDCG: true residual ["<<rhs<<"] is "<<true_residual
<<" solution "<<xnorm
<<" source "<<srcnorm
<<std::endl;
}
return;
}
}
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: PrecBlockCGrQ not converged "<<HDCGTimer.Elapsed()<<std::endl;
assert(0);
}
virtual void SolveSingleSystem (std::vector<Field> &src, std::vector<Field> &x)
{
std::cout << GridLogMessage<<"HDCG: mrhs fPcg starting"<<std::endl;
src[0].Grid()->Barrier();
@ -361,15 +657,23 @@ public:
CoarseField PleftProjMrhs(this->coarsegridmrhs);
CoarseField PleftMss_projMrhs(this->coarsegridmrhs);
#undef SMOOTHER_BLOCK_SOLVE
#if SMOOTHER_BLOCK_SOLVE
this->SmoothTimer.Start();
this->_Smoother(in,Min);
this->SmoothTimer.Stop();
#else
for(int rhs=0;rhs<nrhs;rhs++) {
this->SmoothTimer.Start();
this->_Smoother(in[rhs],Min[rhs]);
this->SmoothTimer.Stop();
}
#endif
for(int rhs=0;rhs<nrhs;rhs++) {
this->FineTimer.Start();
this->_FineLinop.HermOp(Min[rhs],out[rhs]);
axpy(tmp[rhs],-1.0,out[rhs],in[rhs]); // resid = in - A Min
this->FineTimer.Stop();
@ -407,7 +711,7 @@ public:
this->FineTimer.Stop();
}
};
NAMESPACE_END(Grid);

View File

@ -31,6 +31,58 @@ directory
NAMESPACE_BEGIN(Grid);
template<class Field>
void InnerProductMatrix(Eigen::MatrixXcd &m , const std::vector<Field> &X, const std::vector<Field> &Y){
typedef typename Field::scalar_type scomplex;
int Nblock = X.size();
for(int b=0;b<Nblock;b++){
for(int bp=0;bp<Nblock;bp++) {
m(b,bp) = innerProduct(X[b],Y[bp]);
}}
}
template<class Field>
void MaddMatrix(std::vector<Field> &AP, Eigen::MatrixXcd &m , const std::vector<Field> &X,const std::vector<Field> &Y,RealD scale=1.0){
// Should make this cache friendly with site outermost, parallel_for
// Deal with case AP aliases with either Y or X
//
//Could pack "X" and "AP" into a Nblock x Volume dense array.
// AP(Nrhs x vol) = Y(Nrhs x vol) + scale * m(nrhs x nrhs) * X(nrhs*vol)
typedef typename Field::scalar_type scomplex;
int Nblock = AP.size();
std::vector<Field> tmp(Nblock,X[0]);
for(int b=0;b<Nblock;b++){
tmp[b] = Y[b];
for(int bp=0;bp<Nblock;bp++) {
tmp[b] = tmp[b] +scomplex(scale*m(bp,b))*X[bp];
}
}
for(int b=0;b<Nblock;b++){
AP[b] = tmp[b];
}
}
template<class Field>
void MulMatrix(std::vector<Field> &AP, Eigen::MatrixXcd &m , const std::vector<Field> &X){
// Should make this cache friendly with site outermost, parallel_for
typedef typename Field::scalar_type scomplex;
int Nblock = AP.size();
for(int b=0;b<Nblock;b++){
AP[b] = Zero();
for(int bp=0;bp<Nblock;bp++) {
AP[b] += scomplex(m(bp,b))*X[bp];
}
}
}
template<class Field>
double normv(const std::vector<Field> &P){
int Nblock = P.size();
double nn = 0.0;
for(int b=0;b<Nblock;b++) {
nn+=norm2(P[b]);
}
return nn;
}
enum BlockCGtype { BlockCG, BlockCGrQ, CGmultiRHS, BlockCGVec, BlockCGrQVec };
//////////////////////////////////////////////////////////////////////////
@ -87,10 +139,19 @@ void ThinQRfact (Eigen::MatrixXcd &m_rr,
sliceInnerProductMatrix(m_rr,R,R,Orthog);
// Force manifest hermitian to avoid rounding related
/*
int rank=m_rr.rows();
for(int r=0;r<rank;r++){
for(int s=0;s<rank;s++){
std::cout << "QR m_rr["<<r<<","<<s<<"] "<<m_rr(r,s)<<std::endl;
}}
*/
m_rr = 0.5*(m_rr+m_rr.adjoint());
Eigen::MatrixXcd L = m_rr.llt().matrixL();
// ComplexD det = L.determinant();
// std::cout << " Det m_rr "<<det<<std::endl;
C = L.adjoint();
Cinv = C.inverse();
////////////////////////////////////////////////////////////////////////////////////////////////////
@ -110,11 +171,20 @@ void ThinQRfact (Eigen::MatrixXcd &m_rr,
const std::vector<Field> & R)
{
InnerProductMatrix(m_rr,R,R);
/*
int rank=m_rr.rows();
for(int r=0;r<rank;r++){
for(int s=0;s<rank;s++){
std::cout << "QRvec m_rr["<<r<<","<<s<<"] "<<m_rr(r,s)<<std::endl;
}}
*/
m_rr = 0.5*(m_rr+m_rr.adjoint());
Eigen::MatrixXcd L = m_rr.llt().matrixL();
// ComplexD det = L.determinant();
// std::cout << " Det m_rr "<<det<<std::endl;
C = L.adjoint();
Cinv = C.inverse();
@ -186,6 +256,7 @@ void BlockCGrQsolve(LinearOperatorBase<Field> &Linop, const Field &B, Field &X)
sliceNorm(ssq,B,Orthog);
RealD sssum=0;
for(int b=0;b<Nblock;b++) sssum+=ssq[b];
for(int b=0;b<Nblock;b++) std::cout << "src["<<b<<"]" << ssq[b] <<std::endl;
sliceNorm(residuals,B,Orthog);
for(int b=0;b<Nblock;b++){ assert(std::isnan(residuals[b])==0); }
@ -221,6 +292,9 @@ void BlockCGrQsolve(LinearOperatorBase<Field> &Linop, const Field &B, Field &X)
Linop.HermOp(X, AD);
tmp = B - AD;
sliceNorm(residuals,tmp,Orthog);
for(int b=0;b<Nblock;b++) std::cout << "res["<<b<<"]" << residuals[b] <<std::endl;
ThinQRfact (m_rr, m_C, m_Cinv, Q, tmp);
D=Q;
@ -236,6 +310,8 @@ void BlockCGrQsolve(LinearOperatorBase<Field> &Linop, const Field &B, Field &X)
GridStopWatch SolverTimer;
SolverTimer.Start();
RealD max_resid=0;
int k;
for (k = 1; k <= MaxIterations; k++) {
@ -280,7 +356,7 @@ void BlockCGrQsolve(LinearOperatorBase<Field> &Linop, const Field &B, Field &X)
*/
m_rr = m_C.adjoint() * m_C;
RealD max_resid=0;
max_resid=0;
RealD rrsum=0;
RealD rr;
@ -322,7 +398,9 @@ void BlockCGrQsolve(LinearOperatorBase<Field> &Linop, const Field &B, Field &X)
}
}
std::cout << GridLogMessage << "BlockConjugateGradient(rQ) did NOT converge" << std::endl;
std::cout << GridLogMessage << "BlockConjugateGradient(rQ) did NOT converge "<<k<<" / "<<MaxIterations
<<" residual "<< std::sqrt(max_resid)<< std::endl;
if (ErrorOnNoConverge) assert(0);
IterationsToComplete = k;
@ -466,43 +544,6 @@ void CGmultiRHSsolve(LinearOperatorBase<Field> &Linop, const Field &Src, Field &
IterationsToComplete = k;
}
void InnerProductMatrix(Eigen::MatrixXcd &m , const std::vector<Field> &X, const std::vector<Field> &Y){
for(int b=0;b<Nblock;b++){
for(int bp=0;bp<Nblock;bp++) {
m(b,bp) = innerProduct(X[b],Y[bp]);
}}
}
void MaddMatrix(std::vector<Field> &AP, Eigen::MatrixXcd &m , const std::vector<Field> &X,const std::vector<Field> &Y,RealD scale=1.0){
// Should make this cache friendly with site outermost, parallel_for
// Deal with case AP aliases with either Y or X
std::vector<Field> tmp(Nblock,X[0]);
for(int b=0;b<Nblock;b++){
tmp[b] = Y[b];
for(int bp=0;bp<Nblock;bp++) {
tmp[b] = tmp[b] + scomplex(scale*m(bp,b))*X[bp];
}
}
for(int b=0;b<Nblock;b++){
AP[b] = tmp[b];
}
}
void MulMatrix(std::vector<Field> &AP, Eigen::MatrixXcd &m , const std::vector<Field> &X){
// Should make this cache friendly with site outermost, parallel_for
for(int b=0;b<Nblock;b++){
AP[b] = Zero();
for(int bp=0;bp<Nblock;bp++) {
AP[b] += scomplex(m(bp,b))*X[bp];
}
}
}
double normv(const std::vector<Field> &P){
double nn = 0.0;
for(int b=0;b<Nblock;b++) {
nn+=norm2(P[b]);
}
return nn;
}
////////////////////////////////////////////////////////////////////////////
// BlockCGrQvec implementation:
//--------------------------
@ -549,6 +590,7 @@ void BlockCGrQsolveVec(LinearOperatorBase<Field> &Linop, const std::vector<Field
RealD sssum=0;
for(int b=0;b<Nblock;b++){ ssq[b] = norm2(B[b]);}
for(int b=0;b<Nblock;b++){ std::cout << "ssq["<<b<<"] "<<ssq[b]<<std::endl;}
for(int b=0;b<Nblock;b++) sssum+=ssq[b];
for(int b=0;b<Nblock;b++){ residuals[b] = norm2(B[b]);}
@ -585,6 +627,7 @@ void BlockCGrQsolveVec(LinearOperatorBase<Field> &Linop, const std::vector<Field
for(int b=0;b<Nblock;b++) {
Linop.HermOp(X[b], AD[b]);
tmp[b] = B[b] - AD[b];
std::cout << "r0["<<b<<"] "<<norm2(tmp[b])<<std::endl;
}
ThinQRfact (m_rr, m_C, m_Cinv, Q, tmp);

View File

@ -38,12 +38,13 @@ NAMESPACE_BEGIN(Grid);
// single input vec, single output vec.
/////////////////////////////////////////////////////////////
template <class Field>
class ConjugateGradient : public OperatorFunction<Field> {
public:
using OperatorFunction<Field>::operator();
bool ErrorOnNoConverge; // throw an assert when the CG fails to converge.
// Defaults true.
RealD Tolerance;
@ -57,10 +58,22 @@ public:
ErrorOnNoConverge(err_on_no_conv)
{};
void operator()(LinearOperatorBase<Field> &Linop, const Field &src, Field &psi) {
virtual void LogIteration(int k,RealD a,RealD b){
// std::cout << "ConjugageGradient::LogIteration() "<<std::endl;
};
virtual void LogBegin(void){
std::cout << "ConjugageGradient::LogBegin() "<<std::endl;
};
GRID_TRACE("ConjugateGradient");
void operator()(LinearOperatorBase<Field> &Linop, const Field &src, Field &psi) {
this->LogBegin();
GRID_TRACE("ConjugateGradient");
GridStopWatch PreambleTimer;
GridStopWatch ConstructTimer;
GridStopWatch NormTimer;
GridStopWatch AssignTimer;
PreambleTimer.Start();
psi.Checkerboard() = src.Checkerboard();
@ -70,14 +83,19 @@ public:
//RealD b_pred;
// Was doing copies
Field p(src.Grid());
ConstructTimer.Start();
Field p (src.Grid());
Field mmp(src.Grid());
Field r(src.Grid());
Field r (src.Grid());
ConstructTimer.Stop();
// Initial residual computation & set up
NormTimer.Start();
ssq = norm2(src);
RealD guess = norm2(psi);
NormTimer.Stop();
assert(std::isnan(guess) == 0);
AssignTimer.Start();
if ( guess == 0.0 ) {
r = src;
p = r;
@ -89,6 +107,7 @@ public:
a = norm2(p);
}
cp = a;
AssignTimer.Stop();
// Handle trivial case of zero src
if (ssq == 0.){
@ -164,6 +183,7 @@ public:
}
LinearCombTimer.Stop();
LinalgTimer.Stop();
LogIteration(k,a,b);
IterationTimer.Stop();
if ( (k % 500) == 0 ) {
@ -220,6 +240,9 @@ public:
<<" residual "<< std::sqrt(cp / ssq)<< std::endl;
SolverTimer.Stop();
std::cout << GridLogMessage << "\tPreamble " << PreambleTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tConstruct " << ConstructTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tNorm " << NormTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tAssign " << AssignTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tSolver " << SolverTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "Solver breakdown "<<std::endl;
std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
@ -233,5 +256,118 @@ public:
}
};
template <class Field>
class ConjugateGradientPolynomial : public ConjugateGradient<Field> {
public:
// Optionally record the CG polynomial
std::vector<double> ak;
std::vector<double> bk;
std::vector<double> poly_p;
std::vector<double> poly_r;
std::vector<double> poly_Ap;
std::vector<double> polynomial;
public:
ConjugateGradientPolynomial(RealD tol, Integer maxit, bool err_on_no_conv = true)
: ConjugateGradient<Field>(tol,maxit,err_on_no_conv)
{ };
void PolyHermOp(LinearOperatorBase<Field> &Linop, const Field &src, Field &psi)
{
Field tmp(src.Grid());
Field AtoN(src.Grid());
AtoN = src;
psi=AtoN*polynomial[0];
for(int n=1;n<polynomial.size();n++){
tmp = AtoN;
Linop.HermOp(tmp,AtoN);
psi = psi + polynomial[n]*AtoN;
}
}
void CGsequenceHermOp(LinearOperatorBase<Field> &Linop, const Field &src, Field &x)
{
Field Ap(src.Grid());
Field r(src.Grid());
Field p(src.Grid());
p=src;
r=src;
x=Zero();
x.Checkerboard()=src.Checkerboard();
for(int k=0;k<ak.size();k++){
x = x + ak[k]*p;
Linop.HermOp(p,Ap);
r = r - ak[k] * Ap;
p = r + bk[k] * p;
}
}
void Solve(LinearOperatorBase<Field> &Linop, const Field &src, Field &psi)
{
psi=Zero();
this->operator ()(Linop,src,psi);
}
virtual void LogBegin(void)
{
std::cout << "ConjugageGradientPolynomial::LogBegin() "<<std::endl;
ak.resize(0);
bk.resize(0);
polynomial.resize(0);
poly_Ap.resize(0);
poly_Ap.resize(0);
poly_p.resize(1);
poly_r.resize(1);
poly_p[0]=1.0;
poly_r[0]=1.0;
};
virtual void LogIteration(int k,RealD a,RealD b)
{
// With zero guess,
// p = r = src
//
// iterate:
// x = x + a p
// r = r - a A p
// p = r + b p
//
// [0]
// r = x
// p = x
// Ap=0
//
// [1]
// Ap = A x + 0 ==> shift poly P right by 1 and add 0.
// x = x + a p ==> add polynomials term by term
// r = r - a A p ==> add polynomials term by term
// p = r + b p ==> add polynomials term by term
//
std::cout << "ConjugageGradientPolynomial::LogIteration() "<<k<<std::endl;
ak.push_back(a);
bk.push_back(b);
// Ap= right_shift(p)
poly_Ap.resize(k+1);
poly_Ap[0]=0.0;
for(int i=0;i<k;i++){
poly_Ap[i+1]=poly_p[i];
}
// x = x + a p
polynomial.resize(k);
polynomial[k-1]=0.0;
for(int i=0;i<k;i++){
polynomial[i] = polynomial[i] + a * poly_p[i];
}
// r = r - a Ap
// p = r + b p
poly_r.resize(k+1);
poly_p.resize(k+1);
poly_r[k] = poly_p[k] = 0.0;
for(int i=0;i<k+1;i++){
poly_r[i] = poly_r[i] - a * poly_Ap[i];
poly_p[i] = poly_r[i] + b * poly_p[i];
}
}
};
NAMESPACE_END(Grid);
#endif

View File

@ -143,7 +143,7 @@ public:
ip = innerProduct(evec[j],w);
if(if_print)
if( norm(ip)/norm2(w) > 1e-14)
Glog<<"orthogonalize before: "<<j<<" of "<<k<<" "<< ip <<std::endl;
Glog<<"orthogonalize before: "<<j<<" of "<<k<<" "<< ip <<std::endl;
w = w - ip * evec[j];
if(if_print) {
ip = innerProduct(evec[j],w);
@ -279,16 +279,16 @@ public:
Qt = Eigen::MatrixXcd::Identity(Nm,Nm);
diagonalize(eval2,lmd2,lme2,Nu,Nm,Nm,Qt,grid);
_sort.push(eval2,Nm);
Glog << "#Ritz value before shift: "<< std::endl;
// Glog << "#Ritz value before shift: "<< std::endl;
for(int i=0; i<Nm; ++i){
std::cout.precision(13);
std::cout << "[" << std::setw(4)<< std::setiosflags(std::ios_base::right) <<i<<"] ";
std::cout << "Rval = "<<std::setw(20)<< std::setiosflags(std::ios_base::left)<< eval2[i] << std::endl;
// std::cout.precision(13);
// std::cout << "[" << std::setw(4)<< std::setiosflags(std::ios_base::right) <<i<<"] ";
// std::cout << "Rval = "<<std::setw(20)<< std::setiosflags(std::ios_base::left)<< eval2[i] << std::endl;
}
//----------------------------------------------------------------------
if ( Nm>Nk ) {
Glog <<" #Apply shifted QR transformations "<<std::endl;
// Glog <<" #Apply shifted QR transformations "<<std::endl;
//int k2 = Nk+Nu;
int k2 = Nk;
@ -326,11 +326,11 @@ public:
Qt = Eigen::MatrixXcd::Identity(Nm,Nm);
diagonalize(eval2,lmd2,lme2,Nu,Nk,Nm,Qt,grid);
_sort.push(eval2,Nk);
Glog << "#Ritz value after shift: "<< std::endl;
// Glog << "#Ritz value after shift: "<< std::endl;
for(int i=0; i<Nk; ++i){
// std::cout.precision(13);
// std::cout << "[" << std::setw(4)<< std::setiosflags(std::ios_base::right) <<i<<"] ";
// std::cout << "Rval = "<<std::setw(20)<< std::setiosflags(std::ios_base::left)<< eval2[i] << std::endl;
// std::cout.precision(13);
// std::cout << "[" << std::setw(4)<< std::setiosflags(std::ios_base::right) <<i<<"] ";
// std::cout << "Rval = "<<std::setw(20)<< std::setiosflags(std::ios_base::left)<< eval2[i] << std::endl;
}
}
//----------------------------------------------------------------------
@ -644,7 +644,7 @@ private:
// for (int u=0; u<mrhs; ++u) Glog << " out["<<u<<"] = "<<norm2(out[u])<<std::endl;
k_start +=mrhs;
}
Glog << "LinAlg "<< std::endl;
// Glog << "LinAlg "<< std::endl;
if (b>0) {
for (int u=0; u<Nu; ++u) {
@ -678,7 +678,7 @@ private:
}
w_copy[u] = w[u];
}
Glog << "LinAlg done"<< std::endl;
// Glog << "LinAlg done"<< std::endl;
// In block version, the steps 6 and 7 in Lanczos construction is
// replaced by the QR decomposition of new basis block.
@ -691,15 +691,15 @@ private:
}
// re-orthogonalization for numerical stability
Glog << "Gram Schmidt"<< std::endl;
// Glog << "Gram Schmidt"<< std::endl;
orthogonalize(w,Nu,evec,R);
// QR part
for (int u=1; u<Nu; ++u) {
orthogonalize(w[u],w,u);
}
Glog << "Gram Schmidt done "<< std::endl;
// Glog << "Gram Schmidt done "<< std::endl;
Glog << "LinAlg "<< std::endl;
// Glog << "LinAlg "<< std::endl;
for (int u=0; u<Nu; ++u) {
//for (int v=0; v<Nu; ++v) {
for (int v=u; v<Nu; ++v) {
@ -716,7 +716,7 @@ private:
// Glog <<" In block "<< b << "," <<" beta[" << u << "," << k-L << "] = " << lme[u][k] << std::endl;
}
}
Glog << "LinAlg done "<< std::endl;
// Glog << "LinAlg done "<< std::endl;
if (b < Nm/Nu-1) {
for (int u=0; u<Nu; ++u) {
@ -935,7 +935,7 @@ if (1){
int Nu, int Nb, int Nk, int Nm,
Eigen::MatrixXcd& M)
{
Glog << "unpackHermitBlockTriDiagMatToEigen() begin" << '\n';
// Glog << "unpackHermitBlockTriDiagMatToEigen() begin" << '\n';
assert( Nk%Nu == 0 && Nm%Nu == 0 );
assert( Nk <= Nm );
M = Eigen::MatrixXcd::Zero(Nk,Nk);
@ -953,7 +953,7 @@ if (1){
M(u+(k/Nu)*Nu,k-Nu) = lme[u][k-Nu];
}
}
Glog << "unpackHermitBlockTriDiagMatToEigen() end" << std::endl;
// Glog << "unpackHermitBlockTriDiagMatToEigen() end" << std::endl;
}
@ -963,7 +963,7 @@ if (1){
int Nu, int Nb, int Nk, int Nm,
Eigen::MatrixXcd& M)
{
Glog << "packHermitBlockTriDiagMatfromEigen() begin" << '\n';
// Glog << "packHermitBlockTriDiagMatfromEigen() begin" << '\n';
assert( Nk%Nu == 0 && Nm%Nu == 0 );
assert( Nk <= Nm );
@ -979,7 +979,7 @@ if (1){
lme[u][k-Nu] = M(u+(k/Nu)*Nu,k-Nu);
}
}
Glog << "packHermitBlockTriDiagMatfromEigen() end" <<std::endl;
// Glog << "packHermitBlockTriDiagMatfromEigen() end" <<std::endl;
}
@ -988,7 +988,7 @@ if (1){
RealD Dsh,
Eigen::MatrixXcd& Qprod)
{
Glog << "shiftedQRDecompEigen() begin" << '\n';
// Glog << "shiftedQRDecompEigen() begin" << '\n';
Eigen::MatrixXcd Q = Eigen::MatrixXcd::Zero(Nm,Nm);
Eigen::MatrixXcd R = Eigen::MatrixXcd::Zero(Nm,Nm);
Eigen::MatrixXcd Mtmp = Eigen::MatrixXcd::Zero(Nm,Nm);
@ -1004,7 +1004,7 @@ if (1){
// lower triangular part used to represent series
// of Q sequence.
Glog << "shiftedQRDecompEigen() Housholder & QR" << '\n';
// Glog << "shiftedQRDecompEigen() Housholder & QR" << '\n';
// equivalent operation of Qprod *= Q
//M = Eigen::MatrixXcd::Zero(Nm,Nm);
@ -1025,7 +1025,7 @@ if (1){
Mtmp = Eigen::MatrixXcd::Zero(Nm,Nm);
Glog << "shiftedQRDecompEigen() Mtmp create" << '\n';
// Glog << "shiftedQRDecompEigen() Mtmp create" << '\n';
for (int i=0; i<Nm; ++i) {
for (int j=0; j<Nm-(Nu+1); ++j) {
for (int k=0; k<Nu+1+j; ++k) {
@ -1033,7 +1033,7 @@ if (1){
}
}
}
Glog << "shiftedQRDecompEigen() Mtmp loop1" << '\n';
// Glog << "shiftedQRDecompEigen() Mtmp loop1" << '\n';
for (int i=0; i<Nm; ++i) {
for (int j=Nm-(Nu+1); j<Nm; ++j) {
for (int k=0; k<Nm; ++k) {
@ -1041,7 +1041,7 @@ if (1){
}
}
}
Glog << "shiftedQRDecompEigen() Mtmp loop2" << '\n';
// Glog << "shiftedQRDecompEigen() Mtmp loop2" << '\n';
//static int ntimes = 2;
//for (int j=0; j<Nm-(ntimes*Nu); ++j) {
@ -1067,13 +1067,13 @@ if (1){
Mtmp(j,i) = conj(Mtmp(i,j));
}
}
Glog << "shiftedQRDecompEigen() Mtmp loop3" << '\n';
// Glog << "shiftedQRDecompEigen() Mtmp loop3" << '\n';
for (int i=0; i<Nm; ++i) {
Mtmp(i,i) = real(Mtmp(i,i)) + Dsh;
}
Glog << "shiftedQRDecompEigen() Mtmp loop4" << '\n';
// Glog << "shiftedQRDecompEigen() Mtmp loop4" << '\n';
M = Mtmp;
//M = Q.adjoint()*(M*Q);
@ -1085,7 +1085,7 @@ if (1){
// }
//}
Glog << "shiftedQRDecompEigen() end" <<std::endl;
// Glog << "shiftedQRDecompEigen() end" <<std::endl;
}
void exampleQRDecompEigen(void)

View File

@ -60,6 +60,32 @@ public:
}
};
template<class Field> class NormalResidual : public LinearFunction<Field>{
private:
SparseMatrixBase<Field> & _Matrix;
OperatorFunction<Field> & _HermitianSolver;
LinearFunction<Field> & _Guess;
public:
/////////////////////////////////////////////////////
// Wrap the usual normal equations trick
/////////////////////////////////////////////////////
NormalResidual(SparseMatrixBase<Field> &Matrix, OperatorFunction<Field> &HermitianSolver,
LinearFunction<Field> &Guess)
: _Matrix(Matrix), _HermitianSolver(HermitianSolver), _Guess(Guess) {};
void operator() (const Field &in, Field &out){
Field res(in.Grid());
Field tmp(in.Grid());
MMdagLinearOperator<SparseMatrixBase<Field>,Field> MMdagOp(_Matrix);
_Guess(in,res);
_HermitianSolver(MMdagOp,in,res); // M Mdag res = in ;
_Matrix.Mdag(res,out); // out = Mdag res
}
};
template<class Field> class HPDSolver : public LinearFunction<Field> {
private:
LinearOperatorBase<Field> & _Matrix;

View File

@ -20,7 +20,7 @@ template<class Field> class PowerMethod
RealD evalMaxApprox = 0.0;
auto src_n = src;
auto tmp = src;
const int _MAX_ITER_EST_ = 100;
const int _MAX_ITER_EST_ = 200;
for (int i=0;i<_MAX_ITER_EST_;i++) {
@ -30,18 +30,17 @@ template<class Field> class PowerMethod
RealD vden = norm2(src_n);
RealD na = vnum/vden;
std::cout << GridLogIterative << "PowerMethod: Current approximation of largest eigenvalue " << na << std::endl;
std::cout << GridLogMessage << "PowerMethod: Current approximation of largest eigenvalue " << na << std::endl;
if ( (fabs(evalMaxApprox/na - 1.0) < 0.001) || (i==_MAX_ITER_EST_-1) ) {
evalMaxApprox = na;
std::cout << GridLogMessage << " Approximation of largest eigenvalue: " << evalMaxApprox << std::endl;
return evalMaxApprox;
}
// if ( (fabs(evalMaxApprox/na - 1.0) < 0.0001) || (i==_MAX_ITER_EST_-1) ) {
// evalMaxApprox = na;
// return evalMaxApprox;
// }
evalMaxApprox = na;
src_n = tmp;
}
assert(0);
return 0;
std::cout << GridLogMessage << " Approximation of largest eigenvalue: " << evalMaxApprox << std::endl;
return evalMaxApprox;
}
};
}

View File

@ -0,0 +1,76 @@
#pragma once
namespace Grid {
class Band
{
RealD lo, hi;
public:
Band(RealD _lo,RealD _hi)
{
lo=_lo;
hi=_hi;
}
RealD operator() (RealD x){
if ( x>lo && x<hi ){
return 1.0;
} else {
return 0.0;
}
}
};
class PowerSpectrum
{
public:
template<typename T> static RealD normalise(T& v)
{
RealD nn = norm2(v);
nn = sqrt(nn);
v = v * (1.0/nn);
return nn;
}
std::vector<RealD> ranges;
std::vector<int> order;
PowerSpectrum( std::vector<RealD> &bins, std::vector<int> &_order ) : ranges(bins), order(_order) { };
template<class Field>
RealD operator()(LinearOperatorBase<Field> &HermOp, const Field &src)
{
GridBase *grid = src.Grid();
int N=ranges.size();
RealD hi = ranges[N-1];
RealD lo_band = 0.0;
RealD hi_band;
RealD nn=norm2(src);
RealD ss=0.0;
Field tmp = src;
for(int b=0;b<N;b++){
hi_band = ranges[b];
Band Notch(lo_band,hi_band);
Chebyshev<Field> polynomial;
polynomial.Init(0.0,hi,order[b],Notch);
polynomial.JacksonSmooth();
polynomial(HermOp,src,tmp) ;
RealD p=norm2(tmp);
ss=ss+p;
std::cout << GridLogMessage << " PowerSpectrum Band["<<lo_band<<","<<hi_band<<"] power "<<norm2(tmp)/nn<<std::endl;
lo_band=hi_band;
}
std::cout << GridLogMessage << " PowerSpectrum total power "<<ss/nn<<std::endl;
std::cout << GridLogMessage << " PowerSpectrum total power (unnormalised) "<<nn<<std::endl;
return 0;
};
};
}

View File

@ -82,6 +82,7 @@ public:
bool _isCheckerBoarded;
int LocallyPeriodic;
Coordinate _checker_dim_mask;
int _checker_dim;
public:
@ -89,7 +90,7 @@ public:
// Checkerboarding interface is virtual and overridden by
// GridCartesian / GridRedBlackCartesian
////////////////////////////////////////////////////////////////
virtual int CheckerBoarded(int dim)=0;
virtual int CheckerBoarded(int dim) =0;
virtual int CheckerBoard(const Coordinate &site)=0;
virtual int CheckerBoardDestination(int source_cb,int shift,int dim)=0;
virtual int CheckerBoardShift(int source_cb,int dim,int shift,int osite)=0;

View File

@ -38,7 +38,7 @@ class GridCartesian: public GridBase {
public:
int dummy;
Coordinate _checker_dim_mask;
// Coordinate _checker_dim_mask;
virtual int CheckerBoardFromOindexTable (int Oindex) {
return 0;
}
@ -46,7 +46,7 @@ public:
{
return 0;
}
virtual int CheckerBoarded(int dim){
virtual int CheckerBoarded(int dim) {
return 0;
}
virtual int CheckerBoard(const Coordinate &site){
@ -106,6 +106,7 @@ public:
_rdimensions.resize(_ndimension);
_simd_layout.resize(_ndimension);
_checker_dim_mask.resize(_ndimension);;
_checker_dim = -1;
_lstart.resize(_ndimension);
_lend.resize(_ndimension);

View File

@ -57,9 +57,10 @@ class GridRedBlackCartesian : public GridBase
{
public:
// Coordinate _checker_dim_mask;
int _checker_dim;
// int _checker_dim;
std::vector<int> _checker_board;
virtual int isCheckerBoarded(void) const { return 1; };
virtual int CheckerBoarded(int dim){
if( dim==_checker_dim) return 1;
else return 0;
@ -147,7 +148,7 @@ public:
{
Init(base->_fdimensions,base->_simd_layout,base->_processors,checker_dim_mask,checker_dim) ;
}
virtual ~GridRedBlackCartesian() = default;
void Init(const Coordinate &dimensions,

View File

@ -236,17 +236,17 @@ public:
template<class sobj> inline Lattice<vobj> & operator = (const sobj & r){
vobj vtmp;
vtmp = r;
#if 1
auto me = View(CpuWrite);
thread_for(ss,me.size(),{
me[ss]= r;
});
#else
#if defined(GRID_HIP) || defined(GRID_CUDA) || defined (GRID_SYCL)
auto me = View(AcceleratorWrite);
accelerator_for(ss,me.size(),vobj::Nsimd(),{
auto stmp=coalescedRead(vtmp);
coalescedWrite(me[ss],stmp);
});
#else
auto me = View(CpuWrite);
thread_for(ss,me.size(),{
me[ss]= r;
});
#endif
me.ViewClose();
return *this;

View File

@ -165,7 +165,7 @@ inline void peekLocalSite(sobj &s,const LatticeView<vobj> &l,Coordinate &site)
int Nsimd = grid->Nsimd();
assert( l.Checkerboard()== grid->CheckerBoard(site));
// assert( l.Checkerboard()== grid->CheckerBoard(site));
assert( sizeof(sobj)*Nsimd == sizeof(vobj));
static const int words=sizeof(vobj)/sizeof(vector_type);
@ -179,7 +179,7 @@ inline void peekLocalSite(sobj &s,const LatticeView<vobj> &l,Coordinate &site)
for(int w=0;w<words;w++){
pt[w] = getlane(vp[w],idx);
}
// std::cout << "peekLocalSite "<<site<<" "<<odx<<","<<idx<<" "<<s<<std::endl;
return;
};
template<class vobj,class sobj>
@ -202,7 +202,7 @@ inline void pokeLocalSite(const sobj &s,LatticeView<vobj> &l,Coordinate &site)
int Nsimd = grid->Nsimd();
assert( l.Checkerboard()== grid->CheckerBoard(site));
// assert( l.Checkerboard()== grid->CheckerBoard(site));
assert( sizeof(sobj)*Nsimd == sizeof(vobj));
static const int words=sizeof(vobj)/sizeof(vector_type);

View File

@ -519,7 +519,20 @@ sliceSum(const Lattice<vobj> &Data,int orthogdim)
return result;
}
/*
Reimplement
1)
template<class vobj>
static void sliceMaddMatrix (Lattice<vobj> &R,Eigen::MatrixXcd &aa,const Lattice<vobj> &X,const Lattice<vobj> &Y,int Orthog,RealD scale=1.0)
2)
template<class vobj>
static void sliceInnerProductMatrix( Eigen::MatrixXcd &mat, const Lattice<vobj> &lhs,const Lattice<vobj> &rhs,int Orthog)
3)
-- Make Slice Mul Matrix call sliceMaddMatrix
*/
template<class vobj>
static void sliceInnerProductVector( std::vector<ComplexD> & result, const Lattice<vobj> &lhs,const Lattice<vobj> &rhs,int orthogdim)
{
@ -670,203 +683,96 @@ static void sliceMaddVector(Lattice<vobj> &R,std::vector<RealD> &a,const Lattice
}
};
/*
inline GridBase *makeSubSliceGrid(const GridBase *BlockSolverGrid,int Orthog)
{
int NN = BlockSolverGrid->_ndimension;
int nsimd = BlockSolverGrid->Nsimd();
std::vector<int> latt_phys(0);
std::vector<int> simd_phys(0);
std::vector<int> mpi_phys(0);
std::vector<int> latt_phys(NN-1);
Coordinate simd_phys;
std::vector<int> mpi_phys(NN-1);
Coordinate checker_dim_mask(NN-1);
int checker_dim=-1;
int dd;
for(int d=0;d<NN;d++){
if( d!=Orthog ) {
latt_phys.push_back(BlockSolverGrid->_fdimensions[d]);
simd_phys.push_back(BlockSolverGrid->_simd_layout[d]);
mpi_phys.push_back(BlockSolverGrid->_processors[d]);
latt_phys[dd]=BlockSolverGrid->_fdimensions[d];
mpi_phys[dd] =BlockSolverGrid->_processors[d];
checker_dim_mask[dd] = BlockSolverGrid->_checker_dim_mask[d];
if ( d == BlockSolverGrid->_checker_dim ) checker_dim = dd;
dd++;
}
}
return (GridBase *)new GridCartesian(latt_phys,simd_phys,mpi_phys);
simd_phys=GridDefaultSimd(latt_phys.size(),nsimd);
GridCartesian *tmp = new GridCartesian(latt_phys,simd_phys,mpi_phys);
if(BlockSolverGrid->_isCheckerBoarded) {
GridRedBlackCartesian *ret = new GridRedBlackCartesian(tmp,checker_dim_mask,checker_dim);
delete tmp;
return (GridBase *) ret;
} else {
return (GridBase *) tmp;
}
}
*/
template<class vobj>
static void sliceMaddMatrix (Lattice<vobj> &R,Eigen::MatrixXcd &aa,const Lattice<vobj> &X,const Lattice<vobj> &Y,int Orthog,RealD scale=1.0)
{
GridBase *FullGrid = X.Grid();
GridBase *SliceGrid = makeSubSliceGrid(FullGrid,Orthog);
Lattice<vobj> Ys(SliceGrid);
Lattice<vobj> Rs(SliceGrid);
Lattice<vobj> Xs(SliceGrid);
Lattice<vobj> RR(FullGrid);
RR = R; // Copies checkerboard for insert
typedef typename vobj::scalar_object sobj;
typedef typename vobj::vector_type vector_type;
int Nblock = X.Grid()->GlobalDimensions()[Orthog];
GridBase *FullGrid = X.Grid();
// GridBase *SliceGrid = makeSubSliceGrid(FullGrid,Orthog);
// Lattice<vobj> Xslice(SliceGrid);
// Lattice<vobj> Rslice(SliceGrid);
assert( FullGrid->_simd_layout[Orthog]==1);
// int nh = FullGrid->_ndimension;
// int nl = SliceGrid->_ndimension;
// int nl = nh-1;
//FIXME package in a convenient iterator
//Should loop over a plane orthogonal to direction "Orthog"
int stride=FullGrid->_slice_stride[Orthog];
int block =FullGrid->_slice_block [Orthog];
int nblock=FullGrid->_slice_nblock[Orthog];
int ostride=FullGrid->_ostride[Orthog];
autoView( X_v, X, CpuRead);
autoView( Y_v, Y, CpuRead);
autoView( R_v, R, CpuWrite);
thread_region
{
Vector<vobj> s_x(Nblock);
thread_for_collapse_in_region(2, n,nblock, {
for(int b=0;b<block;b++){
int o = n*stride + b;
for(int i=0;i<Nblock;i++){
s_x[i] = X_v[o+i*ostride];
}
vobj dot;
for(int i=0;i<Nblock;i++){
dot = Y_v[o+i*ostride];
for(int j=0;j<Nblock;j++){
dot = dot + s_x[j]*(scale*aa(j,i));
}
R_v[o+i*ostride]=dot;
}
}});
int Nslice = X.Grid()->GlobalDimensions()[Orthog];
for(int i=0;i<Nslice;i++){
ExtractSlice(Ys,Y,i,Orthog);
ExtractSlice(Rs,R,i,Orthog);
Rs=Ys;
for(int j=0;j<Nslice;j++){
ExtractSlice(Xs,X,j,Orthog);
Rs = Rs + Xs*(scale*aa(j,i));
}
InsertSlice(Rs,RR,i,Orthog);
}
R=RR; // Copy back handles arguments aliasing case
delete SliceGrid;
};
template<class vobj>
static void sliceMulMatrix (Lattice<vobj> &R,Eigen::MatrixXcd &aa,const Lattice<vobj> &X,int Orthog,RealD scale=1.0)
{
typedef typename vobj::scalar_object sobj;
typedef typename vobj::vector_type vector_type;
int Nblock = X.Grid()->GlobalDimensions()[Orthog];
GridBase *FullGrid = X.Grid();
// GridBase *SliceGrid = makeSubSliceGrid(FullGrid,Orthog);
// Lattice<vobj> Xslice(SliceGrid);
// Lattice<vobj> Rslice(SliceGrid);
assert( FullGrid->_simd_layout[Orthog]==1);
// int nh = FullGrid->_ndimension;
// int nl = SliceGrid->_ndimension;
// int nl=1;
//FIXME package in a convenient iterator
// thread_for2d_in_region
//Should loop over a plane orthogonal to direction "Orthog"
int stride=FullGrid->_slice_stride[Orthog];
int block =FullGrid->_slice_block [Orthog];
int nblock=FullGrid->_slice_nblock[Orthog];
int ostride=FullGrid->_ostride[Orthog];
autoView( R_v, R, CpuWrite);
autoView( X_v, X, CpuRead);
thread_region
{
std::vector<vobj> s_x(Nblock);
thread_for_collapse_in_region( 2 ,n,nblock,{
for(int b=0;b<block;b++){
int o = n*stride + b;
for(int i=0;i<Nblock;i++){
s_x[i] = X_v[o+i*ostride];
}
vobj dot;
for(int i=0;i<Nblock;i++){
dot = s_x[0]*(scale*aa(0,i));
for(int j=1;j<Nblock;j++){
dot = dot + s_x[j]*(scale*aa(j,i));
}
R_v[o+i*ostride]=dot;
}
}});
}
static void sliceMulMatrix (Lattice<vobj> &R,Eigen::MatrixXcd &aa,const Lattice<vobj> &X,int Orthog,RealD scale=1.0)
{
R=Zero();
sliceMaddMatrix(R,aa,X,R,Orthog,scale);
};
template<class vobj>
static void sliceInnerProductMatrix( Eigen::MatrixXcd &mat, const Lattice<vobj> &lhs,const Lattice<vobj> &rhs,int Orthog)
{
GridBase *SliceGrid = makeSubSliceGrid(lhs.Grid(),Orthog);
Lattice<vobj> ls(SliceGrid);
Lattice<vobj> rs(SliceGrid);
typedef typename vobj::scalar_object sobj;
typedef typename vobj::vector_type vector_type;
GridBase *FullGrid = lhs.Grid();
// GridBase *SliceGrid = makeSubSliceGrid(FullGrid,Orthog);
int Nblock = FullGrid->GlobalDimensions()[Orthog];
// Lattice<vobj> Lslice(SliceGrid);
// Lattice<vobj> Rslice(SliceGrid);
mat = Eigen::MatrixXcd::Zero(Nblock,Nblock);
assert( FullGrid->_simd_layout[Orthog]==1);
// int nh = FullGrid->_ndimension;
// int nl = SliceGrid->_ndimension;
// int nl = nh-1;
//FIXME package in a convenient iterator
//Should loop over a plane orthogonal to direction "Orthog"
int stride=FullGrid->_slice_stride[Orthog];
int block =FullGrid->_slice_block [Orthog];
int nblock=FullGrid->_slice_nblock[Orthog];
int ostride=FullGrid->_ostride[Orthog];
typedef typename vobj::vector_typeD vector_typeD;
autoView( lhs_v, lhs, CpuRead);
autoView( rhs_v, rhs, CpuRead);
thread_region
{
std::vector<vobj> Left(Nblock);
std::vector<vobj> Right(Nblock);
Eigen::MatrixXcd mat_thread = Eigen::MatrixXcd::Zero(Nblock,Nblock);
thread_for_collapse_in_region( 2, n,nblock,{
for(int b=0;b<block;b++){
int o = n*stride + b;
for(int i=0;i<Nblock;i++){
Left [i] = lhs_v[o+i*ostride];
Right[i] = rhs_v[o+i*ostride];
}
for(int i=0;i<Nblock;i++){
for(int j=0;j<Nblock;j++){
auto tmp = innerProduct(Left[i],Right[j]);
auto rtmp = TensorRemove(tmp);
auto red = Reduce(rtmp);
mat_thread(i,j) += std::complex<double>(real(red),imag(red));
}}
}});
thread_critical
{
mat += mat_thread;
}
int Nslice = lhs.Grid()->GlobalDimensions()[Orthog];
mat = Eigen::MatrixXcd::Zero(Nslice,Nslice);
for(int s=0;s<Nslice;s++){
ExtractSlice(ls,lhs,s,Orthog);
for(int ss=0;ss<Nslice;ss++){
ExtractSlice(rs,rhs,ss,Orthog);
mat(s,ss) = innerProduct(ls,rs);
}
}
for(int i=0;i<Nblock;i++){
for(int j=0;j<Nblock;j++){
ComplexD sum = mat(i,j);
FullGrid->GlobalSum(sum);
mat(i,j)=sum;
}}
return;
delete SliceGrid;
}
NAMESPACE_END(Grid);

View File

@ -981,8 +981,14 @@ void InsertSlice(const Lattice<vobj> &lowDim,Lattice<vobj> & higherDim,int slice
hcoor[orthog] = slice;
for(int d=0;d<nh;d++){
if ( d!=orthog ) {
hcoor[d]=lcoor[ddl++];
hcoor[d]=lcoor[ddl];
if ( hg->_checker_dim == d ) {
hcoor[d]=hcoor[d]*2; // factor in the full coor for peekLocalSite
lcoor[ddl]=lcoor[ddl]*2; // factor in the full coor for peekLocalSite
}
ddl++;
}
}
peekLocalSite(s,lowDimv,lcoor);
pokeLocalSite(s,higherDimv,hcoor);
@ -1003,6 +1009,7 @@ void ExtractSlice(Lattice<vobj> &lowDim,const Lattice<vobj> & higherDim,int slic
assert(orthog<nh);
assert(orthog>=0);
assert(hg->_processors[orthog]==1);
lowDim.Checkerboard() = higherDim.Checkerboard();
int dl; dl = 0;
for(int d=0;d<nh;d++){
@ -1020,11 +1027,16 @@ void ExtractSlice(Lattice<vobj> &lowDim,const Lattice<vobj> & higherDim,int slic
Coordinate lcoor(nl);
Coordinate hcoor(nh);
lg->LocalIndexToLocalCoor(idx,lcoor);
int ddl=0;
hcoor[orthog] = slice;
int ddl=0;
for(int d=0;d<nh;d++){
if ( d!=orthog ) {
hcoor[d]=lcoor[ddl++];
hcoor[d]=lcoor[ddl];
if ( hg->_checker_dim == d ) {
hcoor[d]=hcoor[d]*2; // factor in the full gridd coor for peekLocalSite
lcoor[ddl]=lcoor[ddl]*2; // factor in the full coor for peekLocalSite
}
ddl++;
}
}
peekLocalSite(s,higherDimv,hcoor);

View File

@ -33,11 +33,11 @@ export MPICH_OFI_NIC_POLICY=GPU
# 12 ppn, 2 nodes, 24 ranks
#
CMD="mpiexec -np 12 -ppn 12 -envall \
CMD="mpiexec -np 1 -ppn 1 -envall \
./gpu_tile_compact.sh \
./Benchmark_comms_host_device --mpi 2.2.1.3 --grid 24.32.32.24 \
./Benchmark_usqcd --mpi 1.1.1.1 --grid 24.32.32.24 \
--shm-mpi 0 --shm 2048 --device-mem 32000 --accelerator-threads 32"
#$CMD | tee 1node.comms
$CMD | tee usqcd.log
CMD="mpiexec -np 1 -ppn 1 -envall \
@ -50,7 +50,7 @@ CMD="mpiexec -np 12 -ppn 12 -envall \
./gpu_tile_compact.sh \
./Benchmark_dwf_fp32 --mpi 2.2.1.3 --grid 32.32.32.48 \
--shm-mpi 0 --shm 2048 --device-mem 32000 --accelerator-threads 32 --comms-overlap"
$CMD | tee 1node.32.32.32.48.dwf
#$CMD | tee 1node.32.32.32.48.dwf
CMD="mpiexec -np 12 -ppn 12 -envall \

View File

@ -1,6 +1,6 @@
export LDFLAGS="-fiopenmp -fsycl -fsycl-device-code-split=per_kernel -fsycl-targets=spir64_gen -Xs -device -Xs pvc -fsycl-device-lib=all -lze_loader -L${MKLROOT}/lib -qmkl=parallel -fsycl -lsycl "
export CXXFLAGS="-O3 -fiopenmp -fsycl-unnamed-lambda -fsycl -I$INSTALL/include -Wno-tautological-compare -I$HOME/ -qmkl=parallel -fsycl -fno-exceptions -fsycl-targets=spir64_gen -Xs -device -Xs pvc "
export LDFLAGS="-fiopenmp -fsycl -fsycl-device-code-split=per_kernel -fsycl-device-lib=all -lze_loader -L${MKLROOT}/lib -qmkl=parallel -fsycl -lsycl "
export CXXFLAGS="-O3 -fiopenmp -fsycl-unnamed-lambda -fsycl -I$INSTALL/include -Wno-tautological-compare -I$HOME/ -qmkl=parallel -fsycl -fno-exceptions "
../../configure \
--enable-simd=GPU \
--enable-gen-simd-width=64 \

View File

@ -77,13 +77,13 @@ int main (int argc, char ** argv)
{
Grid_init(&argc,&argv);
const int Ls=24;
const int nbasis = 60;
const int Ls=16;
const int nbasis = 40;
const int cb = 0 ;
RealD mass=0.00078;
RealD mass=0.01;
RealD M5=1.8;
RealD b=1.5;
RealD c=0.5;
RealD b=1.0;
RealD c=0.0;
GridCartesian * UGrid = SpaceTimeGrid::makeFourDimGrid(GridDefaultLatt(),
GridDefaultSimd(Nd,vComplex::Nsimd()),
@ -117,7 +117,7 @@ int main (int argc, char ** argv)
LatticeGaugeField Umu(UGrid);
FieldMetaData header;
std::string file("ckpoint_EODWF_lat.125");
std::string file("ckpoint_lat.4000");
NerscIO::readConfiguration(Umu,header,file);
//////////////////////// Fermion action //////////////////////////////////
@ -155,7 +155,7 @@ int main (int argc, char ** argv)
std::cout << "**************************************"<<std::endl;
std::cout << "Refine Subspace"<<std::endl;
std::cout << "**************************************"<<std::endl;
Aggregates.RefineSubspace(HermOpEO,0.001,1.0e-3,3000); // 172 iters
// Aggregates.RefineSubspace(HermOpEO,0.01,1.0e-3,1000);
std::cout << "**************************************"<<std::endl;
std::cout << "Coarsen after refine"<<std::endl;
@ -167,7 +167,7 @@ int main (int argc, char ** argv)
std::cout << "**************************************"<<std::endl;
ConjugateGradient<CoarseVector> coarseCG(4.0e-2,20000,true);
const int nrhs=12;
const int nrhs=8;
Coordinate mpi=GridDefaultMpi();
Coordinate rhMpi ({1,1,mpi[0],mpi[1],mpi[2],mpi[3]});
@ -185,7 +185,7 @@ int main (int argc, char ** argv)
std::cout << "**************************************"<<std::endl;
typedef HermitianLinearOperator<MultiGeneralCoarsenedMatrix_t,CoarseVector> MrhsHermMatrix;
Chebyshev<CoarseVector> IRLCheby(0.01,42.0,301); // 1 iter
Chebyshev<CoarseVector> IRLCheby(0.05,40.0,101); // 1 iter
MrhsHermMatrix MrhsCoarseOp (mrhs);
CoarseVector pm_src(CoarseMrhs);
@ -193,8 +193,10 @@ int main (int argc, char ** argv)
PowerMethod<CoarseVector> cPM;
cPM(MrhsCoarseOp,pm_src);
int Nk=192;
int Nm=384;
int Nk=nrhs;
int Nm=Nk*3;
int Nk=36;
int Nm=144;
int Nstop=Nk;
int Nconv_test_interval=1;
@ -208,7 +210,7 @@ int main (int argc, char ** argv)
nrhs,
Nk,
Nm,
1e-5,10);
1e-4,10);
int Nconv;
std::vector<RealD> eval(Nm);
@ -250,9 +252,9 @@ int main (int argc, char ** argv)
// Extra HDCG parameters
//////////////////////////
int maxit=3000;
ConjugateGradient<CoarseVector> CG(5.0e-2,maxit,false);
ConjugateGradient<CoarseVector> CG(2.0e-1,maxit,false);
RealD lo=2.0;
int ord = 7;
int ord = 9;
DoNothingGuesser<CoarseVector> DoNothing;
HPDSolver<CoarseVector> HPDSolveMrhs(MrhsCoarseOp,CG,DoNothing);

View File

@ -287,8 +287,8 @@ int main (int argc, char ** argv)
} else {
// Aggregates.CreateSubspaceMultishift(RNG5,HermOpEO,
// 0.0003,1.0e-5,2000); // Lo, tol, maxit
Aggregates.CreateSubspaceChebyshev(RNG5,HermOpEO,nbasis,95.,0.01,1500); <== last run
// Aggregates.CreateSubspaceChebyshevNew(RNG5,HermOpEO,95.); // 176 with refinement
// Aggregates.CreateSubspaceChebyshev(RNG5,HermOpEO,nbasis,95.,0.01,1500); <== last run
Aggregates.CreateSubspaceChebyshevNew(RNG5,HermOpEO,95.); // 176 with refinement
// Aggregates.CreateSubspaceChebyshev(RNG5,HermOpEO,nbasis,95.,0.001,3000,1500,200,0.0); // Attempt to resurrect
SaveBasis(Aggregates,subspace_file);
}

View File

@ -0,0 +1,761 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./tests/Test_general_coarse_hdcg.cc
Copyright (C) 2023
Author: Peter Boyle <pboyle@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
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#include <Grid/Grid.h>
#include <Grid/algorithms/iterative/ImplicitlyRestartedBlockLanczos.h>
#include <Grid/algorithms/iterative/ImplicitlyRestartedBlockLanczosCoarse.h>
#include <Grid/algorithms/iterative/AdefMrhs.h>
#include <Grid/algorithms/iterative/PowerSpectrum.h>
#include <Grid/algorithms/iterative/BlockConjugateGradient.h>
using namespace std;
using namespace Grid;
template<class aggregation>
void SaveFineEvecs(aggregation &Agg,std::string file)
{
#ifdef HAVE_LIME
emptyUserRecord record;
ScidacWriter WR(Agg[0].Grid()->IsBoss());
WR.open(file);
for(int b=0;b<Agg.size();b++){
WR.writeScidacFieldRecord(Agg[b],record,0,Grid::BinaryIO::BINARYIO_LEXICOGRAPHIC);
}
WR.close();
#endif
}
template<class aggregation>
void SaveBasis(aggregation &Agg,std::string file)
{
#ifdef HAVE_LIME
emptyUserRecord record;
ScidacWriter WR(Agg.FineGrid->IsBoss());
WR.open(file);
for(int b=0;b<Agg.subspace.size();b++){
WR.writeScidacFieldRecord(Agg.subspace[b],record,0,Grid::BinaryIO::BINARYIO_LEXICOGRAPHIC);
// WR.writeScidacFieldRecord(Agg.subspace[b],record);
}
WR.close();
#endif
}
template<class aggregation>
void LoadBasis(aggregation &Agg, std::string file)
{
#ifdef HAVE_LIME
emptyUserRecord record;
ScidacReader RD ;
RD.open(file);
for(int b=0;b<Agg.subspace.size();b++){
RD.readScidacFieldRecord(Agg.subspace[b],record,Grid::BinaryIO::BINARYIO_LEXICOGRAPHIC);
// RD.readScidacFieldRecord(Agg.subspace[b],record,0);
}
RD.close();
#endif
}
template<class aggregation>
void LoadBasisSkip(aggregation &Agg, std::string file,int N,LatticeFermionF & tmp)
{
#ifdef HAVE_LIME
emptyUserRecord record;
ScidacReader RD ;
RD.open(file);
for(int b=0;b<Agg.subspace.size();b++){
for(int n=0;n<N;n++){
RD.readScidacFieldRecord(tmp,record,Grid::BinaryIO::BINARYIO_LEXICOGRAPHIC);
if(n==0) precisionChange(Agg.subspace[b],tmp);
}
// RD.readScidacFieldRecord(Agg.subspace[b],record,0);
}
RD.close();
#endif
}
template<class aggregation>
void LoadBasisSum(aggregation &Agg, std::string file,int N,LatticeFermionF & tmp)
{
#ifdef HAVE_LIME
emptyUserRecord record;
ScidacReader RD ;
LatticeFermionF sum(tmp.Grid());
RD.open(file);
for(int b=0;b<Agg.subspace.size();b++){
sum=Zero();
for(int n=0;n<N;n++){
RD.readScidacFieldRecord(tmp,record,Grid::BinaryIO::BINARYIO_LEXICOGRAPHIC);
sum=sum+tmp;
}
precisionChange(Agg.subspace[b],sum);
// RD.readScidacFieldRecord(Agg.subspace[b],record,0);
}
RD.close();
#endif
}
template<class CoarseVector>
void SaveEigenvectors(std::vector<RealD> &eval,
std::vector<CoarseVector> &evec,
std::string evec_file,
std::string eval_file)
{
#ifdef HAVE_LIME
emptyUserRecord record;
ScidacWriter WR(evec[0].Grid()->IsBoss());
WR.open(evec_file);
for(int b=0;b<evec.size();b++){
WR.writeScidacFieldRecord(evec[b],record,0,0);
}
WR.close();
XmlWriter WRx(eval_file);
write(WRx,"evals",eval);
#endif
}
template<class CoarseVector>
void LoadEigenvectors(std::vector<RealD> &eval,
std::vector<CoarseVector> &evec,
std::string evec_file,
std::string eval_file)
{
#ifdef HAVE_LIME
XmlReader RDx(eval_file);
read(RDx,"evals",eval);
emptyUserRecord record;
Grid::ScidacReader RD ;
RD.open(evec_file);
assert(evec.size()==eval.size());
for(int k=0;k<eval.size();k++) {
RD.readScidacFieldRecord(evec[k],record);
}
RD.close();
#endif
}
// Want Op in CoarsenOp to call MatPcDagMatPc
template<class Field>
class HermOpAdaptor : public LinearOperatorBase<Field>
{
LinearOperatorBase<Field> & wrapped;
public:
HermOpAdaptor(LinearOperatorBase<Field> &wrapme) : wrapped(wrapme) {};
void Op (const Field &in, Field &out) { wrapped.HermOp(in,out); }
void HermOp(const Field &in, Field &out) { wrapped.HermOp(in,out); }
void AdjOp (const Field &in, Field &out){ wrapped.HermOp(in,out); }
void OpDiag (const Field &in, Field &out) { assert(0); }
void OpDir (const Field &in, Field &out,int dir,int disp) { assert(0); }
void OpDirAll (const Field &in, std::vector<Field> &out) { assert(0); };
void HermOpAndNorm(const Field &in, Field &out,RealD &n1,RealD &n2){ assert(0); }
};
template<class Field> class FixedCGPolynomial : public LinearFunction<Field>
{
public:
using LinearFunction<Field>::operator();
typedef LinearOperatorBase<Field> FineOperator;
FineOperator & _SmootherOperator;
ConjugateGradientPolynomial<Field> CG;
int iters;
bool record;
int replay_count;
FixedCGPolynomial(int _iters, FineOperator &SmootherOperator) :
_SmootherOperator(SmootherOperator),
iters(_iters),
record(true),
CG(0.0,_iters,false)
{
std::cout << GridLogMessage<<" FixedCGPolynomial order "<<iters<<std::endl;
replay_count = 0;
};
void operator() (const Field &in, Field &out)
{
#if 1
GridBase *grid = in.Grid();
Field Mx0(grid);
Field r0(grid);
Field Minvr0(grid);
_SmootherOperator.HermOp(out,Mx0);
r0 = in - Mx0;
Minvr0 = Zero();
Minvr0.Checkerboard()=in.Checkerboard();
if ( record ) {
std::cout << " FixedCGPolynomial recording polynomial "<<std::endl;
CG.Solve(_SmootherOperator,r0,Minvr0);
record = false;
/*
std::cout << "P(x) = 0 "<<std::endl;
for(int i=0;i<CG.polynomial.size();i++){
std::cout<<" + "<< CG.polynomial[i]<<" * (x**"<<i<<")"<<std::endl;
}
*/
Field tmp(Minvr0.Grid());
CG.CGsequenceHermOp(_SmootherOperator,r0,tmp);
tmp = tmp - Minvr0;
std::cout << " CGsequence error "<<norm2(tmp)<<" / "<<norm2(out)<<std::endl;
} else {
std::cout << " FixedCGPolynomial replaying polynomial "<<std::endl;
CG.CGsequenceHermOp(_SmootherOperator,r0,Minvr0);
if ( replay_count %5== 0 ) record=true;
replay_count++;
}
out = out + Minvr0;
_SmootherOperator.HermOp(out,r0);
r0 = r0 - in;
RealD rr=norm2(r0);
RealD ss=norm2(in);
std::cout << " FixedCGPolynomial replayed polynomial resid "<<::sqrt(rr/ss)<<std::endl;
#else
out = Zero();
out.Checkerboard()=in.Checkerboard();
if ( record ) {
std::cout << " FixedCGPolynomial recording polynomial "<<std::endl;
CG.Solve(_SmootherOperator,in,out);
record = false;
std::cout << "P(x) = 0 "<<std::endl;
for(int i=0;i<CG.polynomial.size();i++){
std::cout<<" + "<< CG.polynomial[i]<<" * (x**"<<i<<")"<<std::endl;
}
Field tmp(in.Grid());
CG.CGsequenceHermOp(_SmootherOperator,in,tmp);
tmp = tmp - out;
std::cout << " CGsequence error "<<norm2(tmp)<<" / "<<norm2(out)<<std::endl;
} else {
std::cout << " FixedCGPolynomial replaying polynomial "<<std::endl;
CG.CGsequenceHermOp(_SmootherOperator,in,out);
if ( replay_count %5== 5 ) record=true;
replay_count++;
}
#endif
}
void operator() (const std::vector<Field> &in, std::vector<Field> &out)
{
for(int i=0;i<out.size();i++){
out[i]=Zero();
}
int blockDim = 0;//not used for BlockCGVec
BlockConjugateGradient<Field> BCGV (BlockCGrQVec,blockDim,0.0,iters,false);
BCGV(_SmootherOperator,in,out);
}
};
template<class Field> class CGSmoother : public LinearFunction<Field>
{
public:
using LinearFunction<Field>::operator();
typedef LinearOperatorBase<Field> FineOperator;
FineOperator & _SmootherOperator;
int iters;
CGSmoother(int _iters, FineOperator &SmootherOperator) :
_SmootherOperator(SmootherOperator),
iters(_iters)
{
std::cout << GridLogMessage<<" Mirs smoother order "<<iters<<std::endl;
};
void operator() (const Field &in, Field &out)
{
ConjugateGradient<Field> CG(0.0,iters,false); // non-converge is just fine in a smoother
out=Zero();
CG(_SmootherOperator,in,out);
}
};
RealD InverseApproximation(RealD x){
return 1.0/x;
}
template<class Field> class ChebyshevSmoother : public LinearFunction<Field>
{
public:
using LinearFunction<Field>::operator();
typedef LinearOperatorBase<Field> FineOperator;
FineOperator & _SmootherOperator;
Chebyshev<Field> Cheby;
ChebyshevSmoother(RealD _lo,RealD _hi,int _ord, FineOperator &SmootherOperator) :
_SmootherOperator(SmootherOperator),
Cheby(_lo,_hi,_ord,InverseApproximation)
{
std::cout << GridLogMessage<<" Chebyshev smoother order "<<_ord<<" ["<<_lo<<","<<_hi<<"]"<<std::endl;
};
void operator() (const Field &in, Field &out)
{
// Field r(out.Grid());
Cheby(_SmootherOperator,in,out);
// _SmootherOperator.HermOp(out,r);
// r=r-in;
// RealD rr=norm2(r);
// RealD ss=norm2(in);
// std::cout << GridLogMessage<<" Chebyshev smoother resid "<<::sqrt(rr/ss)<<std::endl;
}
};
template<class Field> class ChebyshevInverter : public LinearFunction<Field>
{
public:
using LinearFunction<Field>::operator();
typedef LinearOperatorBase<Field> FineOperator;
FineOperator & _Operator;
Chebyshev<Field> Cheby;
ChebyshevInverter(RealD _lo,RealD _hi,int _ord, FineOperator &Operator) :
_Operator(Operator),
Cheby(_lo,_hi,_ord,InverseApproximation)
{
std::cout << GridLogMessage<<" Chebyshev Inverter order "<<_ord<<" ["<<_lo<<","<<_hi<<"]"<<std::endl;
};
void operator() (const Field &in, Field &out)
{
Field r(in.Grid());
Field AinvR(in.Grid());
_Operator.HermOp(out,r);
r = in - r; // b - A x
Cheby(_Operator,r,AinvR); // A^{-1} ( b - A x ) ~ A^{-1} b - x
out = out + AinvR;
_Operator.HermOp(out,r);
r = in - r; // b - A x
RealD rr = norm2(r);
RealD ss = norm2(in);
std::cout << "ChebshevInverse resid " <<::sqrt(rr/ss)<<std::endl;
}
};
int main (int argc, char ** argv)
{
Grid_init(&argc,&argv);
int sample=1;
if( GridCmdOptionExists(argv,argv+argc,"--sample") ){
std::string arg;
arg = GridCmdOptionPayload(argv,argv+argc,"--sample");
GridCmdOptionInt(arg,sample);
}
const int Ls=24;
const int nbasis = 64;
const int cb = 0 ;
RealD mass=0.00078;
if( GridCmdOptionExists(argv,argv+argc,"--mass") ){
std::string arg;
arg = GridCmdOptionPayload(argv,argv+argc,"--mass");
GridCmdOptionFloat(arg,mass);
}
RealD M5=1.8;
RealD b=1.5;
RealD c=0.5;
std::cout << GridLogMessage << " *************************** " <<std::endl;
std::cout << GridLogMessage << " Mass " <<mass<<std::endl;
std::cout << GridLogMessage << " M5 " <<M5<<std::endl;
std::cout << GridLogMessage << " Ls " <<Ls<<std::endl;
std::cout << GridLogMessage << " b " <<b<<std::endl;
std::cout << GridLogMessage << " c " <<c<<std::endl;
std::cout << GridLogMessage << " *************************** " <<std::endl;
GridCartesian * UGrid = SpaceTimeGrid::makeFourDimGrid(GridDefaultLatt(),
GridDefaultSimd(Nd,vComplex::Nsimd()),
GridDefaultMpi());
GridRedBlackCartesian * UrbGrid = SpaceTimeGrid::makeFourDimRedBlackGrid(UGrid);
GridCartesian * FGrid = SpaceTimeGrid::makeFiveDimGrid(Ls,UGrid);
GridRedBlackCartesian * FrbGrid = SpaceTimeGrid::makeFiveDimRedBlackGrid(Ls,UGrid);
//////////////////////////////////////////
// Single precision grids -- lanczos + smoother
//////////////////////////////////////////
GridCartesian * UGridF = SpaceTimeGrid::makeFourDimGrid(GridDefaultLatt(),
GridDefaultSimd(Nd,vComplexF::Nsimd()),
GridDefaultMpi());
GridRedBlackCartesian * UrbGridF = SpaceTimeGrid::makeFourDimRedBlackGrid(UGridF);
GridCartesian * FGridF = SpaceTimeGrid::makeFiveDimGrid(Ls,UGridF);
GridRedBlackCartesian * FrbGridF = SpaceTimeGrid::makeFiveDimRedBlackGrid(Ls,UGridF);
///////////////////////// Configuration /////////////////////////////////
LatticeGaugeField Umu(UGrid);
FieldMetaData header;
std::string file("ckpoint_lat.1000");
NerscIO::readConfiguration(Umu,header,file);
//////////////////////// Fermion action //////////////////////////////////
MobiusFermionD Ddwf(Umu,*FGrid,*FrbGrid,*UGrid,*UrbGrid,mass,M5,b,c);
SchurDiagMooeeOperator<MobiusFermionD, LatticeFermion> HermOpEO(Ddwf);
std::cout << "**************************************"<<std::endl;
std::cout << " Fine Power method "<<std::endl;
std::cout << "**************************************"<<std::endl;
{
LatticeFermionD pm_src(FrbGrid);
pm_src = ComplexD(1.0);
PowerMethod<LatticeFermionD> fPM;
fPM(HermOpEO,pm_src);
}
if(0)
{
std::cout << "**************************************"<<std::endl;
std::cout << " Fine Lanczos "<<std::endl;
std::cout << "**************************************"<<std::endl;
typedef LatticeFermionF FermionField;
LatticeGaugeFieldF UmuF(UGridF);
precisionChange(UmuF,Umu);
MobiusFermionF DdwfF(UmuF,*FGridF,*FrbGridF,*UGridF,*UrbGridF,mass,M5,b,c);
SchurDiagMooeeOperator<MobiusFermionF, LatticeFermionF> HermOpEOF(DdwfF);
const int Fine_Nstop = 200;
const int Fine_Nk = 200;
const int Fine_Np = 200;
const int Fine_Nm = Fine_Nk+Fine_Np;
const int Fine_MaxIt= 10;
RealD Fine_resid = 1.0e-4;
std::cout << GridLogMessage << "Fine Lanczos "<<std::endl;
std::cout << GridLogMessage << "Nstop "<<Fine_Nstop<<std::endl;
std::cout << GridLogMessage << "Nk "<<Fine_Nk<<std::endl;
std::cout << GridLogMessage << "Np "<<Fine_Np<<std::endl;
std::cout << GridLogMessage << "resid "<<Fine_resid<<std::endl;
Chebyshev<FermionField> Cheby(0.002,92.0,401);
// Chebyshev<FermionField> Cheby(0.1,92.0,401);
FunctionHermOp<FermionField> OpCheby(Cheby,HermOpEOF);
PlainHermOp<FermionField> Op (HermOpEOF);
ImplicitlyRestartedLanczos<FermionField> IRL(OpCheby,Op,Fine_Nstop,Fine_Nk,Fine_Nm,Fine_resid,Fine_MaxIt);
std::vector<RealD> Fine_eval(Fine_Nm);
FermionField Fine_src(FrbGridF);
Fine_src = ComplexF(1.0);
std::vector<FermionField> Fine_evec(Fine_Nm,FrbGridF);
int Fine_Nconv;
std::cout << GridLogMessage <<" Calling IRL.calc single prec"<<std::endl;
IRL.calc(Fine_eval,Fine_evec,Fine_src,Fine_Nconv);
std::string evec_file("/lustre/orion/phy157/proj-shared/phy157_dwf/paboyle/Subspace.phys48.evecF");
SaveFineEvecs(Fine_evec,evec_file);
}
//////////////////////////////////////////
// Construct a coarsened grid with 4^4 cell
//////////////////////////////////////////
Coordinate Block({4,4,6,4});
Coordinate clatt = GridDefaultLatt();
for(int d=0;d<clatt.size();d++){
clatt[d] = clatt[d]/Block[d];
}
GridCartesian *Coarse4d = SpaceTimeGrid::makeFourDimGrid(clatt,
GridDefaultSimd(Nd,vComplex::Nsimd()),
GridDefaultMpi());;
GridCartesian *Coarse5d = SpaceTimeGrid::makeFiveDimGrid(1,Coarse4d);
///////////////////////// RNGs /////////////////////////////////
std::vector<int> seeds4({1,2,3,4});
std::vector<int> seeds5({5,6,7,8});
std::vector<int> cseeds({5,6,7,8});
GridParallelRNG RNG5(FGrid); RNG5.SeedFixedIntegers(seeds5);
GridParallelRNG RNG4(UGrid); RNG4.SeedFixedIntegers(seeds4);
GridParallelRNG CRNG(Coarse5d);CRNG.SeedFixedIntegers(cseeds);
typedef HermOpAdaptor<LatticeFermionD> HermFineMatrix;
HermFineMatrix FineHermOp(HermOpEO);
////////////////////////////////////////////////////////////
///////////// Coarse basis and Little Dirac Operator ///////
////////////////////////////////////////////////////////////
typedef GeneralCoarsenedMatrix<vSpinColourVector,vTComplex,nbasis> LittleDiracOperator;
typedef LittleDiracOperator::CoarseVector CoarseVector;
NextToNextToNextToNearestStencilGeometry5D geom(Coarse5d);
typedef Aggregation<vSpinColourVector,vTComplex,nbasis> Subspace;
Subspace Aggregates(Coarse5d,FrbGrid,cb);
////////////////////////////////////////////////////////////
// Need to check about red-black grid coarsening
////////////////////////////////////////////////////////////
std::string subspace_file("/lustre/orion/phy157/proj-shared/phy157_dwf/paboyle/Subspace.phys48.mixed.2500.60");
// // std::string subspace_file("/lustre/orion/phy157/proj-shared/phy157_dwf/paboyle/Subspace.phys48.new.62");
std::string refine_file("/lustre/orion/phy157/proj-shared/phy157_dwf/paboyle/Subspace.phys48.evecF");
// std::string refine_file("/lustre/orion/phy157/proj-shared/phy157_dwf/paboyle/Refine.phys48.mixed.2500.60");
std::string ldop_file("/lustre/orion/phy157/proj-shared/phy157_dwf/paboyle/LittleDiracOp.phys48.mixed.60");
std::string evec_file("/lustre/orion/phy157/proj-shared/phy157_dwf/paboyle/evecs.scidac");
std::string eval_file("/lustre/orion/phy157/proj-shared/phy157_dwf/paboyle/eval.xml");
bool load_agg=true;
bool load_refine=true;
bool load_mat=false;
bool load_evec=false;
int refine=1;
if ( load_agg ) {
if ( !(refine) || (!load_refine) ) {
LoadBasis(Aggregates,subspace_file);
}
} else {
// Aggregates.CreateSubspaceMultishift(RNG5,HermOpEO,
// 0.0003,1.0e-5,2000); // Lo, tol, maxit
// Aggregates.CreateSubspaceChebyshev(RNG5,HermOpEO,nbasis,95.,0.01,1500);// <== last run
Aggregates.CreateSubspaceChebyshevNew(RNG5,HermOpEO,95.);
SaveBasis(Aggregates,subspace_file);
}
std::cout << "**************************************"<<std::endl;
std::cout << "Building MultiRHS Coarse operator"<<std::endl;
std::cout << "**************************************"<<std::endl;
ConjugateGradient<CoarseVector> coarseCG(4.0e-2,20000,true);
const int nrhs=12;
Coordinate mpi=GridDefaultMpi();
Coordinate rhMpi ({1,1,mpi[0],mpi[1],mpi[2],mpi[3]});
Coordinate rhLatt({nrhs,1,clatt[0],clatt[1],clatt[2],clatt[3]});
Coordinate rhSimd({vComplex::Nsimd(),1, 1,1,1,1});
GridCartesian *CoarseMrhs = new GridCartesian(rhLatt,rhSimd,rhMpi);
typedef MultiGeneralCoarsenedMatrix<vSpinColourVector,vTComplex,nbasis> MultiGeneralCoarsenedMatrix_t;
MultiGeneralCoarsenedMatrix_t mrhs(geom,CoarseMrhs);
std::cout << "**************************************"<<std::endl;
std::cout << " Coarse Lanczos "<<std::endl;
std::cout << "**************************************"<<std::endl;
typedef HermitianLinearOperator<MultiGeneralCoarsenedMatrix_t,CoarseVector> MrhsHermMatrix;
Chebyshev<CoarseVector> IRLCheby(0.005,42.0,301); // 1 iter
MrhsHermMatrix MrhsCoarseOp (mrhs);
// CoarseVector pm_src(CoarseMrhs);
// pm_src = ComplexD(1.0);
// PowerMethod<CoarseVector> cPM; cPM(MrhsCoarseOp,pm_src);
int Nk=192;
int Nm=384;
int Nstop=Nk;
int Nconv_test_interval=1;
ImplicitlyRestartedBlockLanczosCoarse<CoarseVector> IRL(MrhsCoarseOp,
Coarse5d,
CoarseMrhs,
nrhs,
IRLCheby,
Nstop,
Nconv_test_interval,
nrhs,
Nk,
Nm,
1e-5,10);
int Nconv;
std::vector<RealD> eval(Nm);
std::vector<CoarseVector> evec(Nm,Coarse5d);
std::vector<CoarseVector> c_src(nrhs,Coarse5d);
///////////////////////
// Deflation guesser object
///////////////////////
MultiRHSDeflation<CoarseVector> MrhsGuesser;
//////////////////////////////////////////
// Block projector for coarse/fine
//////////////////////////////////////////
MultiRHSBlockProject<LatticeFermionD> MrhsProjector;
//////////////////////////
// Extra HDCG parameters
//////////////////////////
int maxit=300;
ConjugateGradient<CoarseVector> CG(5.0e-2,maxit,false);
ConjugateGradient<CoarseVector> CGstart(5.0e-2,maxit,false);
RealD lo=2.0;
int ord = 7;
// int ord = 11;
int blockDim = 0;//not used for BlockCG
BlockConjugateGradient<CoarseVector> BCG (BlockCGrQ,blockDim,5.0e-5,maxit,true);
DoNothingGuesser<CoarseVector> DoNothing;
// HPDSolver<CoarseVector> HPDSolveMrhs(MrhsCoarseOp,CG,DoNothing);
// HPDSolver<CoarseVector> HPDSolveMrhsStart(MrhsCoarseOp,CGstart,DoNothing);
// HPDSolver<CoarseVector> HPDSolveMrhs(MrhsCoarseOp,BCG,DoNothing);
// HPDSolver<CoarseVector> HPDSolveMrhsRefine(MrhsCoarseOp,BCG,DoNothing);
// FixedCGPolynomial<CoarseVector> HPDSolveMrhs(maxit,MrhsCoarseOp);
ChebyshevInverter<CoarseVector> HPDSolveMrhs(1.0e-2,40.0,120,MrhsCoarseOp); //
// ChebyshevInverter<CoarseVector> HPDSolveMrhs(1.0e-2,40.0,110,MrhsCoarseOp); // 114 iter with Chebysmooth and BlockCG
// ChebyshevInverter<CoarseVector> HPDSolveMrhs(1.0e-2,40.0,120,MrhsCoarseOp); // 138 iter with Chebysmooth
// ChebyshevInverter<CoarseVector> HPDSolveMrhs(1.0e-2,40.0,200,MrhsCoarseOp); // 139 iter
// ChebyshevInverter<CoarseVector> HPDSolveMrhs(3.0e-3,40.0,200,MrhsCoarseOp); // 137 iter, CG smooth, flex
// ChebyshevInverter<CoarseVector> HPDSolveMrhs(1.0e-3,40.0,200,MrhsCoarseOp); // 146 iter, CG smooth, flex
// ChebyshevInverter<CoarseVector> HPDSolveMrhs(3.0e-4,40.0,200,MrhsCoarseOp); // 156 iter, CG smooth, flex
/////////////////////////////////////////////////
// Mirs smoother
/////////////////////////////////////////////////
ShiftedHermOpLinearOperator<LatticeFermionD> ShiftedFineHermOp(HermOpEO,lo);
// FixedCGPolynomial<LatticeFermionD> CGsmooth(ord,ShiftedFineHermOp) ;
// CGSmoother<LatticeFermionD> CGsmooth(ord,ShiftedFineHermOp) ;
ChebyshevSmoother<LatticeFermionD> CGsmooth(2.0,92.0,8,HermOpEO) ;
if ( load_refine ) {
//LoadBasis(Aggregates,refine_file);
LatticeFermionF conv_tmp(FrbGridF);
LoadBasisSum(Aggregates,refine_file,sample,conv_tmp);
} else {
Aggregates.RefineSubspace(HermOpEO,0.001,1.0e-3,3000); // 172 iters
SaveBasis(Aggregates,refine_file);
}
Aggregates.Orthogonalise();
std::cout << "**************************************"<<std::endl;
std::cout << "Coarsen after refine"<<std::endl;
std::cout << "**************************************"<<std::endl;
mrhs.CoarsenOperator(FineHermOp,Aggregates,Coarse5d);
std::cout << "**************************************"<<std::endl;
std::cout << " Recompute coarse evecs "<<std::endl;
std::cout << "**************************************"<<std::endl;
evec.resize(Nm,Coarse5d);
eval.resize(Nm);
for(int r=0;r<nrhs;r++){
random(CRNG,c_src[r]);
}
IRL.calc(eval,evec,c_src,Nconv,LanczosType::irbl);
std::cout << "**************************************"<<std::endl;
std::cout << " Reimport coarse evecs "<<std::endl;
std::cout << "**************************************"<<std::endl;
MrhsGuesser.ImportEigenBasis(evec,eval);
std::cout << "**************************************"<<std::endl;
std::cout << " Setting up mRHS HDCG"<<std::endl;
std::cout << "**************************************"<<std::endl;
MrhsProjector.Allocate(nbasis,FrbGrid,Coarse5d);
MrhsProjector.ImportBasis(Aggregates.subspace);
std::cout << "**************************************"<<std::endl;
std::cout << "Calling mRHS HDCG"<<std::endl;
std::cout << "**************************************"<<std::endl;
TwoLevelADEF2mrhs<LatticeFermion,CoarseVector>
HDCGmrhs(1.0e-8, 300,
FineHermOp,
CGsmooth,
HPDSolveMrhs, // Used in M1
HPDSolveMrhs, // Used in Vstart
MrhsProjector,
MrhsGuesser,
CoarseMrhs);
std::vector<LatticeFermionD> src_mrhs(nrhs,FrbGrid);
std::vector<LatticeFermionD> res_mrhs(nrhs,FrbGrid);
LatticeFermionD result_accurate(FrbGrid);
LatticeFermionD result_sloppy(FrbGrid);
LatticeFermionD error(FrbGrid);
LatticeFermionD residual(FrbGrid);
for(int r=0;r<nrhs;r++){
random(RNG5,src_mrhs[r]);
res_mrhs[r]=Zero();
}
HDCGmrhs(src_mrhs,res_mrhs);
result_accurate = res_mrhs[0];
#if 0
std::vector<RealD> tols({1.0e-3,1.0e-4,1.0e-5});
std::vector<RealD> bins({1.0e-3,1.0e-2,1.0e-1,1.0,10.0,100.0});
std::vector<int> orders({6000 ,4000 ,1000 ,500,500 ,500});
PowerSpectrum GraphicEqualizer(bins,orders);
for(auto tol : tols) {
TwoLevelADEF2mrhs<LatticeFermion,CoarseVector>
HDCGmrhsSloppy(tol, 500,
FineHermOp,
CGsmooth,
HPDSolveMrhs, // Used in M1
HPDSolveMrhs, // Used in Vstart
MrhsProjector,
MrhsGuesser,
CoarseMrhs);
// Solve again to 10^-5
for(int r=0;r<nrhs;r++){
res_mrhs[r]=Zero();
}
HDCGmrhsSloppy(src_mrhs,res_mrhs);
result_sloppy = res_mrhs[0];
error = result_sloppy - result_accurate;
FineHermOp.HermOp(result_sloppy,residual);
residual = residual - src_mrhs[0];
std::cout << "**************************************"<<std::endl;
std::cout << GridLogMessage << " Converged to tolerance "<< tol<<std::endl;
std::cout << GridLogMessage << " Absolute error "<<norm2(error)<<std::endl;
std::cout << GridLogMessage << " Residual "<<norm2(residual)<<std::endl;
std::cout << "**************************************"<<std::endl;
std::cout << "**************************************"<<std::endl;
std::cout << GridLogMessage << " PowerSpectrum of error "<<std::endl;
std::cout << "**************************************"<<std::endl;
GraphicEqualizer(FineHermOp,error);
std::cout << "**************************************"<<std::endl;
std::cout << GridLogMessage << " PowerSpectrum of residual "<<std::endl;
std::cout << "**************************************"<<std::endl;
GraphicEqualizer(FineHermOp,residual);
};
#endif
// Standard CG
#if 0
{
std::cout << "**************************************"<<std::endl;
std::cout << "Calling red black CG"<<std::endl;
std::cout << "**************************************"<<std::endl;
LatticeFermion result(FrbGrid); result=Zero();
LatticeFermion src(FrbGrid); random(RNG5,src);
result=Zero();
ConjugateGradient<LatticeFermionD> CGfine(1.0e-8,30000,false);
CGfine(HermOpEO, src, result);
}
#endif
Grid_finalize();
return 0;
}