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10 Commits

Author SHA1 Message Date
bae0f8ea99 Merge pull request #425 from rrhodgson/feature/CacheLogging
Huge Cache
2023-03-21 08:59:08 -04:00
bbbcd36ae5 Merge pull request #426 from rrhodgson/feature/LCDeflation
Batched Local Coherence Tools
2023-03-21 08:58:40 -04:00
39c0815d9e WriteDiscard 2023-03-21 08:57:29 -04:00
a3e935c902 Batched block project/promote size checks 2023-02-27 11:38:16 +00:00
7731c7db8e Add huge cache type and allow Ncache==0 2023-02-26 14:15:28 +00:00
ff97340324 Expose cached bytes 2023-02-26 12:22:45 +00:00
920a51438d Added batched Mixed precision CG 2023-02-14 17:04:13 +00:00
be528b6d27 Add batched block project/promote functions 2023-02-14 14:37:10 +00:00
796abfad80 Merge pull request #422 from fjosw/fix/NVCC_DIAG_PRAGMA_SUPPORT
Disable diagnostic pragma warnings for CUDA 12+
2023-01-17 09:34:49 -05:00
ad0270ac8c fix: diagnostic pragma warnings fixed for CUDA 12+ 2023-01-12 12:36:30 +00:00
11 changed files with 312 additions and 222 deletions

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@ -45,7 +45,7 @@ directory
//disables nvcc specific warning in json.hpp
#pragma clang diagnostic ignored "-Wdeprecated-register"
#if (__CUDACC_VER_MAJOR__ >= 11) && (__CUDACC_VER_MINOR__ >= 5)
#ifdef __NVCC_DIAG_PRAGMA_SUPPORT__
//disables nvcc specific warning in json.hpp
#pragma nv_diag_suppress unsigned_compare_with_zero
#pragma nv_diag_suppress cast_to_qualified_type

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@ -14,7 +14,7 @@
/* NVCC save and restore compile environment*/
#ifdef __NVCC__
#pragma push
#if (__CUDACC_VER_MAJOR__ >= 11) && (__CUDACC_VER_MINOR__ >= 5)
#ifdef __NVCC_DIAG_PRAGMA_SUPPORT__
#pragma nv_diag_suppress code_is_unreachable
#else
#pragma diag_suppress code_is_unreachable

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@ -54,6 +54,7 @@ NAMESPACE_CHECK(BiCGSTAB);
#include <Grid/algorithms/iterative/SchurRedBlack.h>
#include <Grid/algorithms/iterative/ConjugateGradientMultiShift.h>
#include <Grid/algorithms/iterative/ConjugateGradientMixedPrec.h>
#include <Grid/algorithms/iterative/ConjugateGradientMixedPrecBatched.h>
#include <Grid/algorithms/iterative/BiCGSTABMixedPrec.h>
#include <Grid/algorithms/iterative/BlockConjugateGradient.h>
#include <Grid/algorithms/iterative/ConjugateGradientReliableUpdate.h>

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@ -0,0 +1,213 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ConjugateGradientMixedPrecBatched.h
Copyright (C) 2015
Author: Raoul Hodgson <raoul.hodgson@ed.ac.uk>
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 */
#ifndef GRID_CONJUGATE_GRADIENT_MIXED_PREC_BATCHED_H
#define GRID_CONJUGATE_GRADIENT_MIXED_PREC_BATCHED_H
NAMESPACE_BEGIN(Grid);
//Mixed precision restarted defect correction CG
template<class FieldD,class FieldF,
typename std::enable_if< getPrecision<FieldD>::value == 2, int>::type = 0,
typename std::enable_if< getPrecision<FieldF>::value == 1, int>::type = 0>
class MixedPrecisionConjugateGradientBatched : public LinearFunction<FieldD> {
public:
using LinearFunction<FieldD>::operator();
RealD Tolerance;
RealD InnerTolerance; //Initial tolerance for inner CG. Defaults to Tolerance but can be changed
Integer MaxInnerIterations;
Integer MaxOuterIterations;
Integer MaxPatchupIterations;
GridBase* SinglePrecGrid; //Grid for single-precision fields
RealD OuterLoopNormMult; //Stop the outer loop and move to a final double prec solve when the residual is OuterLoopNormMult * Tolerance
LinearOperatorBase<FieldF> &Linop_f;
LinearOperatorBase<FieldD> &Linop_d;
//Option to speed up *inner single precision* solves using a LinearFunction that produces a guess
LinearFunction<FieldF> *guesser;
bool updateResidual;
MixedPrecisionConjugateGradientBatched(RealD tol,
Integer maxinnerit,
Integer maxouterit,
Integer maxpatchit,
GridBase* _sp_grid,
LinearOperatorBase<FieldF> &_Linop_f,
LinearOperatorBase<FieldD> &_Linop_d,
bool _updateResidual=true) :
Linop_f(_Linop_f), Linop_d(_Linop_d),
Tolerance(tol), InnerTolerance(tol), MaxInnerIterations(maxinnerit), MaxOuterIterations(maxouterit), MaxPatchupIterations(maxpatchit), SinglePrecGrid(_sp_grid),
OuterLoopNormMult(100.), guesser(NULL), updateResidual(_updateResidual) { };
void useGuesser(LinearFunction<FieldF> &g){
guesser = &g;
}
void operator() (const FieldD &src_d_in, FieldD &sol_d){
std::vector<FieldD> srcs_d_in{src_d_in};
std::vector<FieldD> sols_d{sol_d};
(*this)(srcs_d_in,sols_d);
sol_d = sols_d[0];
}
void operator() (const std::vector<FieldD> &src_d_in, std::vector<FieldD> &sol_d){
assert(src_d_in.size() == sol_d.size());
int NBatch = src_d_in.size();
std::cout << GridLogMessage << "NBatch = " << NBatch << std::endl;
Integer TotalOuterIterations = 0; //Number of restarts
std::vector<Integer> TotalInnerIterations(NBatch,0); //Number of inner CG iterations
std::vector<Integer> TotalFinalStepIterations(NBatch,0); //Number of CG iterations in final patch-up step
GridStopWatch TotalTimer;
TotalTimer.Start();
GridStopWatch InnerCGtimer;
GridStopWatch PrecChangeTimer;
int cb = src_d_in[0].Checkerboard();
std::vector<RealD> src_norm;
std::vector<RealD> norm;
std::vector<RealD> stop;
GridBase* DoublePrecGrid = src_d_in[0].Grid();
FieldD tmp_d(DoublePrecGrid);
tmp_d.Checkerboard() = cb;
FieldD tmp2_d(DoublePrecGrid);
tmp2_d.Checkerboard() = cb;
std::vector<FieldD> src_d;
std::vector<FieldF> src_f;
std::vector<FieldF> sol_f;
for (int i=0; i<NBatch; i++) {
sol_d[i].Checkerboard() = cb;
src_norm.push_back(norm2(src_d_in[i]));
norm.push_back(0.);
stop.push_back(src_norm[i] * Tolerance*Tolerance);
src_d.push_back(src_d_in[i]); //source for next inner iteration, computed from residual during operation
src_f.push_back(SinglePrecGrid);
src_f[i].Checkerboard() = cb;
sol_f.push_back(SinglePrecGrid);
sol_f[i].Checkerboard() = cb;
}
RealD inner_tol = InnerTolerance;
ConjugateGradient<FieldF> CG_f(inner_tol, MaxInnerIterations);
CG_f.ErrorOnNoConverge = false;
Integer &outer_iter = TotalOuterIterations; //so it will be equal to the final iteration count
for(outer_iter = 0; outer_iter < MaxOuterIterations; outer_iter++){
std::cout << GridLogMessage << std::endl;
std::cout << GridLogMessage << "Outer iteration " << outer_iter << std::endl;
bool allConverged = true;
for (int i=0; i<NBatch; i++) {
//Compute double precision rsd and also new RHS vector.
Linop_d.HermOp(sol_d[i], tmp_d);
norm[i] = axpy_norm(src_d[i], -1., tmp_d, src_d_in[i]); //src_d is residual vector
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradientBatched: Outer iteration " << outer_iter <<" solve " << i << " residual "<< norm[i] << " target "<< stop[i] <<std::endl;
PrecChangeTimer.Start();
precisionChange(src_f[i], src_d[i]);
PrecChangeTimer.Stop();
sol_f[i] = Zero();
if(norm[i] > OuterLoopNormMult * stop[i]) {
allConverged = false;
}
}
if (allConverged) break;
if (updateResidual) {
RealD normMax = *std::max_element(std::begin(norm), std::end(norm));
RealD stopMax = *std::max_element(std::begin(stop), std::end(stop));
while( normMax * inner_tol * inner_tol < stopMax) inner_tol *= 2; // inner_tol = sqrt(stop/norm) ??
CG_f.Tolerance = inner_tol;
}
//Optionally improve inner solver guess (eg using known eigenvectors)
if(guesser != NULL) {
(*guesser)(src_f, sol_f);
}
for (int i=0; i<NBatch; i++) {
//Inner CG
InnerCGtimer.Start();
CG_f(Linop_f, src_f[i], sol_f[i]);
InnerCGtimer.Stop();
TotalInnerIterations[i] += CG_f.IterationsToComplete;
//Convert sol back to double and add to double prec solution
PrecChangeTimer.Start();
precisionChange(tmp_d, sol_f[i]);
PrecChangeTimer.Stop();
axpy(sol_d[i], 1.0, tmp_d, sol_d[i]);
}
}
//Final trial CG
std::cout << GridLogMessage << std::endl;
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradientBatched: Starting final patch-up double-precision solve"<<std::endl;
for (int i=0; i<NBatch; i++) {
ConjugateGradient<FieldD> CG_d(Tolerance, MaxPatchupIterations);
CG_d(Linop_d, src_d_in[i], sol_d[i]);
TotalFinalStepIterations[i] += CG_d.IterationsToComplete;
}
TotalTimer.Stop();
std::cout << GridLogMessage << std::endl;
for (int i=0; i<NBatch; i++) {
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradientBatched: solve " << i << " Inner CG iterations " << TotalInnerIterations[i] << " Restarts " << TotalOuterIterations << " Final CG iterations " << TotalFinalStepIterations[i] << std::endl;
}
std::cout << GridLogMessage << std::endl;
std::cout<<GridLogMessage<<"MixedPrecisionConjugateGradientBatched: Total time " << TotalTimer.Elapsed() << " Precision change " << PrecChangeTimer.Elapsed() << " Inner CG total " << InnerCGtimer.Elapsed() << std::endl;
}
};
NAMESPACE_END(Grid);
#endif

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@ -4,11 +4,14 @@ NAMESPACE_BEGIN(Grid);
/*Allocation types, saying which pointer cache should be used*/
#define Cpu (0)
#define CpuSmall (1)
#define Acc (2)
#define AccSmall (3)
#define Shared (4)
#define SharedSmall (5)
#define CpuHuge (1)
#define CpuSmall (2)
#define Acc (3)
#define AccHuge (4)
#define AccSmall (5)
#define Shared (6)
#define SharedHuge (7)
#define SharedSmall (8)
#undef GRID_MM_VERBOSE
uint64_t total_shared;
uint64_t total_device;
@ -35,12 +38,14 @@ void MemoryManager::PrintBytes(void)
}
uint64_t MemoryManager::DeviceCacheBytes() { return CacheBytes[Acc] + CacheBytes[AccHuge] + CacheBytes[AccSmall]; }
//////////////////////////////////////////////////////////////////////
// Data tables for recently freed pooiniter caches
//////////////////////////////////////////////////////////////////////
MemoryManager::AllocationCacheEntry MemoryManager::Entries[MemoryManager::NallocType][MemoryManager::NallocCacheMax];
int MemoryManager::Victim[MemoryManager::NallocType];
int MemoryManager::Ncache[MemoryManager::NallocType] = { 2, 8, 8, 16, 8, 16 };
int MemoryManager::Ncache[MemoryManager::NallocType] = { 2, 0, 8, 8, 0, 16, 8, 0, 16 };
uint64_t MemoryManager::CacheBytes[MemoryManager::NallocType];
//////////////////////////////////////////////////////////////////////
// Actual allocation and deallocation utils
@ -170,6 +175,16 @@ void MemoryManager::Init(void)
}
}
str= getenv("GRID_ALLOC_NCACHE_HUGE");
if ( str ) {
Nc = atoi(str);
if ( (Nc>=0) && (Nc < NallocCacheMax)) {
Ncache[CpuHuge]=Nc;
Ncache[AccHuge]=Nc;
Ncache[SharedHuge]=Nc;
}
}
str= getenv("GRID_ALLOC_NCACHE_SMALL");
if ( str ) {
Nc = atoi(str);
@ -190,7 +205,9 @@ void MemoryManager::InitMessage(void) {
std::cout << GridLogMessage<< "MemoryManager::Init() setting up"<<std::endl;
#ifdef ALLOCATION_CACHE
std::cout << GridLogMessage<< "MemoryManager::Init() cache pool for recent allocations: SMALL "<<Ncache[CpuSmall]<<" LARGE "<<Ncache[Cpu]<<std::endl;
std::cout << GridLogMessage<< "MemoryManager::Init() cache pool for recent host allocations: SMALL "<<Ncache[CpuSmall]<<" LARGE "<<Ncache[Cpu]<<" HUGE "<<Ncache[CpuHuge]<<std::endl;
std::cout << GridLogMessage<< "MemoryManager::Init() cache pool for recent device allocations: SMALL "<<Ncache[AccSmall]<<" LARGE "<<Ncache[Acc]<<" Huge "<<Ncache[AccHuge]<<std::endl;
std::cout << GridLogMessage<< "MemoryManager::Init() cache pool for recent shared allocations: SMALL "<<Ncache[SharedSmall]<<" LARGE "<<Ncache[Shared]<<" Huge "<<Ncache[SharedHuge]<<std::endl;
#endif
#ifdef GRID_UVM
@ -222,8 +239,11 @@ void MemoryManager::InitMessage(void) {
void *MemoryManager::Insert(void *ptr,size_t bytes,int type)
{
#ifdef ALLOCATION_CACHE
bool small = (bytes < GRID_ALLOC_SMALL_LIMIT);
int cache = type + small;
int cache;
if (bytes < GRID_ALLOC_SMALL_LIMIT) cache = type + 2;
else if (bytes >= GRID_ALLOC_HUGE_LIMIT) cache = type + 1;
else cache = type;
return Insert(ptr,bytes,Entries[cache],Ncache[cache],Victim[cache],CacheBytes[cache]);
#else
return ptr;
@ -232,11 +252,12 @@ void *MemoryManager::Insert(void *ptr,size_t bytes,int type)
void *MemoryManager::Insert(void *ptr,size_t bytes,AllocationCacheEntry *entries,int ncache,int &victim, uint64_t &cacheBytes)
{
assert(ncache>0);
#ifdef GRID_OMP
assert(omp_in_parallel()==0);
#endif
if (ncache == 0) return ptr;
void * ret = NULL;
int v = -1;
@ -271,8 +292,11 @@ void *MemoryManager::Insert(void *ptr,size_t bytes,AllocationCacheEntry *entries
void *MemoryManager::Lookup(size_t bytes,int type)
{
#ifdef ALLOCATION_CACHE
bool small = (bytes < GRID_ALLOC_SMALL_LIMIT);
int cache = type+small;
int cache;
if (bytes < GRID_ALLOC_SMALL_LIMIT) cache = type + 2;
else if (bytes >= GRID_ALLOC_HUGE_LIMIT) cache = type + 1;
else cache = type;
return Lookup(bytes,Entries[cache],Ncache[cache],CacheBytes[cache]);
#else
return NULL;
@ -281,7 +305,6 @@ void *MemoryManager::Lookup(size_t bytes,int type)
void *MemoryManager::Lookup(size_t bytes,AllocationCacheEntry *entries,int ncache,uint64_t & cacheBytes)
{
assert(ncache>0);
#ifdef GRID_OMP
assert(omp_in_parallel()==0);
#endif

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@ -35,6 +35,7 @@ NAMESPACE_BEGIN(Grid);
// Move control to configure.ac and Config.h?
#define GRID_ALLOC_SMALL_LIMIT (4096)
#define GRID_ALLOC_HUGE_LIMIT (2147483648)
#define STRINGIFY(x) #x
#define TOSTRING(x) STRINGIFY(x)
@ -83,7 +84,7 @@ private:
} AllocationCacheEntry;
static const int NallocCacheMax=128;
static const int NallocType=6;
static const int NallocType=9;
static AllocationCacheEntry Entries[NallocType][NallocCacheMax];
static int Victim[NallocType];
static int Ncache[NallocType];
@ -122,6 +123,8 @@ private:
static uint64_t DeviceEvictions;
static uint64_t DeviceDestroy;
static uint64_t DeviceCacheBytes();
private:
#ifndef GRID_UVM
//////////////////////////////////////////////////////////////////////

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@ -129,7 +129,7 @@ public:
auto exprCopy = expr;
ExpressionViewOpen(exprCopy);
auto me = View(AcceleratorWrite);
auto me = View(AcceleratorWriteDiscard);
accelerator_for(ss,me.size(),vobj::Nsimd(),{
auto tmp = eval(ss,exprCopy);
coalescedWrite(me[ss],tmp);
@ -152,7 +152,7 @@ public:
auto exprCopy = expr;
ExpressionViewOpen(exprCopy);
auto me = View(AcceleratorWrite);
auto me = View(AcceleratorWriteDiscard);
accelerator_for(ss,me.size(),vobj::Nsimd(),{
auto tmp = eval(ss,exprCopy);
coalescedWrite(me[ss],tmp);
@ -174,7 +174,7 @@ public:
this->checkerboard=cb;
auto exprCopy = expr;
ExpressionViewOpen(exprCopy);
auto me = View(AcceleratorWrite);
auto me = View(AcceleratorWriteDiscard);
accelerator_for(ss,me.size(),vobj::Nsimd(),{
auto tmp = eval(ss,exprCopy);
coalescedWrite(me[ss],tmp);
@ -288,8 +288,8 @@ public:
typename std::enable_if<!std::is_same<robj,vobj>::value,int>::type i=0;
conformable(*this,r);
this->checkerboard = r.Checkerboard();
auto me = View(AcceleratorWrite);
auto him= r.View(AcceleratorRead);
auto me = View(AcceleratorWriteDiscard);
accelerator_for(ss,me.size(),vobj::Nsimd(),{
coalescedWrite(me[ss],him(ss));
});
@ -303,8 +303,8 @@ public:
inline Lattice<vobj> & operator = (const Lattice<vobj> & r){
this->checkerboard = r.Checkerboard();
conformable(*this,r);
auto me = View(AcceleratorWrite);
auto him= r.View(AcceleratorRead);
auto me = View(AcceleratorWriteDiscard);
accelerator_for(ss,me.size(),vobj::Nsimd(),{
coalescedWrite(me[ss],him(ss));
});

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@ -1,126 +0,0 @@
NAMESPACE_BEGIN(Grid);
// If NOT CUDA or HIP -- we should provide
// -- atomicAdd(float *,float)
// -- atomicAdd(double *,double)
//
// Augment CUDA with complex atomics
#if !defined(GRID_HIP) || !defined(GRID_CUDA)
inline void atomicAdd(float *acc,float elem)
{
*acc += elem;
}
inline void atomicAdd(double *acc,double elem)
{
*acc += elem;
}
#endif
inline void atomicAdd(ComplexD *accum,ComplexD & elem)
{
double *a_p = (double *)accum;
double *e_p = (double *)&elem;
for(int w=0;w<2;w++){
atomicAdd(&a_p[w],e_p[w]);
}
}
inline void atomicAdd(ComplexF *accum,ComplexF & elem)
{
float *a_p = (float *)accum;
float *e_p = (float *)&elem;
for(int w=0;w<2;w++){
atomicAdd(&a_p[w],e_p[w]);
}
}
// Augment CUDA with vobj atomics
template<class vobj> accelerator_inline void atomicAdd(vobj *accum, vobj & elem)
{
typedef typename vobj::scalar_type scalar_type;
scalar_type *a_p= (scalar_type *)accum;
scalar_type *e_p= (scalar_type *)& elem;
for(int w=0;w<vobj::Nsimd();w++){
atomicAdd(&a_p[w],e_p[w]);
}
}
// Atomics based slice sum
template<class vobj> inline void sliceSumGpu(const Lattice<vobj> &Data,std::vector<typename vobj::scalar_object> &result,int orthogdim)
{
typedef typename vobj::scalar_object sobj;
typedef typename vobj::scalar_object::scalar_type scalar_type;
GridBase *grid = Data.Grid();
assert(grid!=NULL);
const int Nd = grid->_ndimension;
const int Nsimd = grid->Nsimd();
assert(orthogdim >= 0);
assert(orthogdim < Nd);
int fd=grid->_fdimensions[orthogdim];
int ld=grid->_ldimensions[orthogdim];
int rd=grid->_rdimensions[orthogdim];
// Move to device memory and copy in / out
Vector<vobj> lvSum(rd); // will locally sum vectors first
Vector<sobj> lsSum(ld,Zero()); // sum across these down to scalars
ExtractBuffer<sobj> extracted(Nsimd); // splitting the SIMD
result.resize(fd); // And then global sum to return the same vector to every node
for(int r=0;r<rd;r++){
lvSum[r]=Zero();
}
int e1= grid->_slice_nblock[orthogdim];
int e2= grid->_slice_block [orthogdim];
int stride=grid->_slice_stride[orthogdim];
// sum over reduced dimension planes, breaking out orthog dir
// Parallel over orthog direction
autoView( Data_v, Data, AcceleratorRead);
auto lvSum_p=&lvSum[0];
int ostride = grid->_ostride[orthogdim];
accelerator_for( ree,rd*e1*e2,1, {
int b = ree%e2;
int re= ree/e2;
int n=re%e1;
int r=re/e1;
int so=r*ostride;
int ss=so+n*stride+b;
atomicAdd(&lvSum_p[r],Data_v[ss]);
});
// Sum across simd lanes in the plane, breaking out orthog dir.
Coordinate icoor(Nd);
for(int rt=0;rt<rd;rt++){
extract(lvSum[rt],extracted);
for(int idx=0;idx<Nsimd;idx++){
grid->iCoorFromIindex(icoor,idx);
int ldx =rt+icoor[orthogdim]*rd;
lsSum[ldx]=lsSum[ldx]+extracted[idx];
}
}
// sum over nodes.
for(int t=0;t<fd;t++){
int pt = t/ld; // processor plane
int lt = t%ld;
if ( pt == grid->_processor_coor[orthogdim] ) {
result[t]=lsSum[lt];
} else {
result[t]=Zero();
}
}
scalar_type * ptr = (scalar_type *) &result[0];
int words = fd*sizeof(sobj)/sizeof(scalar_type);
grid->GlobalSumVector(ptr, words);
}
NAMESPACE_END(Grid);

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@ -288,7 +288,36 @@ inline void blockProject(Lattice<iVector<CComplex,nbasis > > &coarseData,
blockZAXPY(fineDataRed,ip,Basis[v],fineDataRed);
}
}
template<class vobj,class CComplex,int nbasis,class VLattice>
inline void batchBlockProject(std::vector<Lattice<iVector<CComplex,nbasis>>> &coarseData,
const std::vector<Lattice<vobj>> &fineData,
const VLattice &Basis)
{
int NBatch = fineData.size();
assert(coarseData.size() == NBatch);
GridBase * fine = fineData[0].Grid();
GridBase * coarse= coarseData[0].Grid();
Lattice<iScalar<CComplex>> ip(coarse);
std::vector<Lattice<vobj>> fineDataCopy = fineData;
autoView(ip_, ip, AcceleratorWrite);
for(int v=0;v<nbasis;v++) {
for (int k=0; k<NBatch; k++) {
autoView( coarseData_ , coarseData[k], AcceleratorWrite);
blockInnerProductD(ip,Basis[v],fineDataCopy[k]); // ip = <basis|fine>
accelerator_for( sc, coarse->oSites(), vobj::Nsimd(), {
convertType(coarseData_[sc](v),ip_[sc]);
});
// improve numerical stability of projection
// |fine> = |fine> - <basis|fine> |basis>
ip=-ip;
blockZAXPY(fineDataCopy[k],ip,Basis[v],fineDataCopy[k]);
}
}
}
template<class vobj,class vobj2,class CComplex>
inline void blockZAXPY(Lattice<vobj> &fineZ,
@ -590,6 +619,26 @@ inline void blockPromote(const Lattice<iVector<CComplex,nbasis > > &coarseData,
}
#endif
template<class vobj,class CComplex,int nbasis,class VLattice>
inline void batchBlockPromote(const std::vector<Lattice<iVector<CComplex,nbasis>>> &coarseData,
std::vector<Lattice<vobj>> &fineData,
const VLattice &Basis)
{
int NBatch = coarseData.size();
assert(fineData.size() == NBatch);
GridBase * fine = fineData[0].Grid();
GridBase * coarse = coarseData[0].Grid();
for (int k=0; k<NBatch; k++)
fineData[k]=Zero();
for (int i=0;i<nbasis;i++) {
for (int k=0; k<NBatch; k++) {
Lattice<iScalar<CComplex>> ip = PeekIndex<0>(coarseData[k],i);
blockZAXPY(fineData[k],ip,Basis[i],fineData[k]);
}
}
}
// Useful for precision conversion, or indeed anything where an operator= does a conversion on scalars.
// Simd layouts need not match since we use peek/poke Local
template<class vobj,class vvobj>

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@ -16,7 +16,7 @@
#ifdef __NVCC__
#pragma push
#if (__CUDACC_VER_MAJOR__ >= 11) && (__CUDACC_VER_MINOR__ >= 5)
#ifdef __NVCC_DIAG_PRAGMA_SUPPORT__
#pragma nv_diag_suppress declared_but_not_referenced // suppress "function was declared but never referenced warning"
#else
#pragma diag_suppress declared_but_not_referenced // suppress "function was declared but never referenced warning"

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@ -1,73 +0,0 @@
/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./tests/Test_poisson_fft.cc
Copyright (C) 2015
Author: Azusa Yamaguchi <ayamaguc@staffmail.ed.ac.uk>
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
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/lattice/Lattice_slice_gpu.h>
using namespace Grid;
int main (int argc, char ** argv)
{
Grid_init(&argc,&argv);
int N=16;
std::vector<int> latt_size ({N,N,N,N});
std::vector<int> simd_layout({vComplexD::Nsimd(),1,1,1});
std::vector<int> mpi_layout ({1,1,1,1});
GridCartesian GRID(latt_size,simd_layout,mpi_layout);
LatticeComplexD rn(&GRID);
GridParallelRNG RNG(&GRID);
RNG.SeedFixedIntegers(std::vector<int>({45,12,81,9}));
gaussian(RNG,rn);
std::vector<TComplex> reduced_ref;
std::vector<TComplex> reduced_gpu;
for(int d=0;d<4;d++){
{
RealD t=-usecond();
sliceSum(rn,reduced_ref,d);
t+=usecond();
std::cout << " sliceSum took "<<t<<" usecs"<<std::endl;
}
{
RealD t=-usecond();
sliceSumGpu(rn,reduced_gpu,d);
t+=usecond();
std::cout << " sliceSumGpu took "<<t<<" usecs"<<std::endl;
}
for(int t=0;t<reduced_ref.size();t++){
std::cout << t<<" ref "<< reduced_ref[t] <<" opt " << reduced_gpu[t] << " diff "<<reduced_ref[t]-reduced_gpu[t]<<std::endl;
TComplex diff = reduced_ref[t]-reduced_gpu[t];
assert(abs(TensorRemove(diff)) < 1e-8 );
}
}
Grid_finalize();
}