1
0
mirror of https://github.com/paboyle/Grid.git synced 2024-11-09 23:45:36 +00:00

Reduction finished and hopefully fixes CI regression fail on single precisoin and force

This commit is contained in:
Peter Boyle 2019-08-14 15:18:34 +01:00
parent 96ac56cace
commit 3e49dc8a67
2 changed files with 119 additions and 73 deletions

View File

@ -29,55 +29,58 @@ Author: paboyle <paboyle@ph.ed.ac.uk>
#endif
NAMESPACE_BEGIN(Grid);
template<class vobj>
inline typename vobj::scalar_object sum_cpu(const Lattice<vobj> &arg)
{
GridBase *grid=arg.Grid();
int Nsimd = grid->Nsimd();
Vector<vobj> sumarray(grid->SumArraySize());
for(int i=0;i<grid->SumArraySize();i++){
//////////////////////////////////////////////////////
// FIXME this should promote to double and accumulate
//////////////////////////////////////////////////////
template<class vobj>
inline typename vobj::scalar_object sum_cpu(const vobj *arg, Integer osites)
{
typedef typename vobj::scalar_object sobj;
const int Nsimd = vobj::Nsimd();
const int nthread = GridThread::GetThreads();
Vector<sobj> sumarray(nthread);
for(int i=0;i<nthread;i++){
sumarray[i]=Zero();
}
auto arg_v=arg.View();
thread_for(thr,grid->SumArraySize(), {
thread_for(thr,nthread, {
int nwork, mywork, myoff;
nwork = grid->oSites();
nwork = osites;
GridThread::GetWork(nwork,thr,mywork,myoff);
vobj vvsum=Zero();
for(int ss=myoff;ss<mywork+myoff; ss++){
vvsum = vvsum + arg_v[ss];
vvsum = vvsum + arg[ss];
}
sumarray[thr]=vvsum;
sumarray[thr]=Reduce(vvsum);
});
vobj vsum=Zero(); // sum across threads
for(int i=0;i<grid->SumArraySize();i++){
vsum = vsum+sumarray[i];
sobj ssum=Zero(); // sum across threads
for(int i=0;i<nthread;i++){
ssum = ssum+sumarray[i];
}
typedef typename vobj::scalar_object sobj;
sobj ssum=Zero();
ExtractBuffer<sobj> buf(Nsimd);
extract(vsum,buf);
for(int i=0;i<Nsimd;i++) ssum = ssum + buf[i];
arg.Grid()->GlobalSum(ssum);
return ssum;
}
template<class vobj>
inline typename vobj::scalar_object sum(const vobj *arg, Integer osites)
{
#ifdef GRID_NVCC
return sum_gpu(arg,osites);
#else
return sum_cpu(arg,osites);
#endif
}
template<class vobj>
inline typename vobj::scalar_object sum(const Lattice<vobj> &arg)
{
#ifdef GRID_NVCC
return sum_gpu(arg);
#else
return sum_cpu(arg);
#endif
auto arg_v = arg.View();
Integer osites = arg.Grid()->oSites();
auto ssum= sum(&arg_v[0],osites);
arg.Grid()->GlobalSum(ssum);
return ssum;
}
////////////////////////////////////////////////////////////////////////////////////////////////////
@ -94,7 +97,7 @@ inline ComplexD innerProduct(const Lattice<vobj> &left,const Lattice<vobj> &righ
{
typedef typename vobj::scalar_type scalar_type;
typedef typename vobj::vector_typeD vector_type;
scalar_type nrm;
ComplexD nrm;
GridBase *grid = left.Grid();
@ -105,9 +108,17 @@ inline ComplexD innerProduct(const Lattice<vobj> &left,const Lattice<vobj> &righ
const uint64_t nsimd = grid->Nsimd();
const uint64_t sites = grid->oSites();
typename vobj::scalar_object f;
typename vobj::scalar_objectD d;
f=Zero();
d=f;
#ifdef GRID_NVCC
// GPU - SIMT lane compliance...
typedef decltype(innerProduct(left_v[0],right_v[0])) inner_t;
Lattice<inner_t> inner_tmp(grid);
auto inner_tmp_v = inner_tmp.View();
Vector<inner_t> inner_tmp(sites);
auto inner_tmp_v = &inner_tmp[0];
accelerator_for( ss, sites, nsimd,{
auto x_l = left_v(ss);
@ -115,9 +126,24 @@ inline ComplexD innerProduct(const Lattice<vobj> &left,const Lattice<vobj> &righ
coalescedWrite(inner_tmp_v[ss],innerProduct(x_l,y_l));
})
nrm = TensorRemove(sum(inner_tmp));
// This is in single precision and fails some tests
// Need a sumD that sums in double
nrm = TensorRemove(sumD_gpu(inner_tmp_v,sites));
#else
// CPU
typedef decltype(innerProductD(left_v[0],right_v[0])) inner_t;
Vector<inner_t> inner_tmp(sites);
auto inner_tmp_v = &inner_tmp[0];
accelerator_for( ss, sites, nsimd,{
auto x_l = left_v[ss];
auto y_l = right_v[ss];
inner_tmp_v[ss]=innerProductD(x_l,y_l);
})
nrm = TensorRemove(sum(inner_tmp_v,sites));
#endif
grid->GlobalSum(nrm);
// right.Grid()->GlobalSum(nrm);
return nrm;
}
@ -153,19 +179,34 @@ axpby_norm_fast(Lattice<vobj> &z,sobj a,sobj b,const Lattice<vobj> &x,const Latt
const uint64_t nsimd = grid->Nsimd();
const uint64_t sites = grid->oSites();
#ifdef GRID_NVCC
// GPU
typedef decltype(innerProduct(x_v[0],y_v[0])) inner_t;
Lattice<inner_t> inner_tmp(grid);
auto inner_tmp_v = inner_tmp.View();
Vector<inner_t> inner_tmp(sites);
auto inner_tmp_v = &inner_tmp[0];
accelerator_for( ss, sites, nsimd,{
auto tmp = a*x_v(ss)+b*y_v(ss);
coalescedWrite(inner_tmp_v[ss],innerProduct(tmp,tmp));
coalescedWrite(z_v[ss],tmp);
})
});
nrm = real(TensorRemove(sum(inner_tmp)));
nrm = real(TensorRemove(sumD_gpu(inner_tmp_v,sites)));
#else
// CPU
typedef decltype(innerProductD(x_v[0],y_v[0])) inner_t;
Vector<inner_t> inner_tmp(sites);
auto inner_tmp_v = &inner_tmp[0];
// z.Grid()->GlobalSum(nrm);
accelerator_for( ss, sites, nsimd,{
auto tmp = a*x_v(ss)+b*y_v(ss);
inner_tmp_v[ss]=innerProductD(tmp,tmp);
z_v[ss]=tmp;
});
// Already promoted to double
nrm = real(TensorRemove(sum(inner_tmp_v,sites)));
#endif
grid->GlobalSum(nrm);
return nrm;
}

View File

@ -82,13 +82,11 @@ __device__ void reduceBlock(volatile sobj *sdata, sobj mySum, const Iterator tid
__syncthreads();
}
template <class vobj, class Iterator>
__device__ void reduceBlocks(const LatticeView<vobj> g_idata, typename vobj::scalar_object *g_odata, Iterator n) {
typedef typename vobj::scalar_type scalar_type;
typedef typename vobj::vector_type vector_type;
typedef typename vobj::scalar_object sobj;
constexpr Iterator nsimd = sizeof(vector_type)/sizeof(scalar_type);
template <class vobj, class sobj, class Iterator>
__device__ void reduceBlocks(const vobj *g_idata, sobj *g_odata, Iterator n)
{
constexpr Iterator nsimd = vobj::Nsimd();
Iterator blockSize = blockDim.x;
@ -109,13 +107,16 @@ __device__ void reduceBlocks(const LatticeView<vobj> g_idata, typename vobj::sca
Iterator lane = i % nsimd;
Iterator ss = i / nsimd;
auto tmp = extractLane(lane,g_idata[ss]);
mySum += tmp;
sobj tmpD;
tmpD=tmp;
mySum +=tmpD;
if (i + blockSize < n) {
lane = (i+blockSize) % nsimd;
ss = (i+blockSize) / nsimd;
tmp = extractLane(lane,g_idata[ss]);
mySum += tmp;
tmpD = tmp;
mySum += tmpD;
}
i += gridSize;
}
@ -126,9 +127,8 @@ __device__ void reduceBlocks(const LatticeView<vobj> g_idata, typename vobj::sca
if (tid == 0) g_odata[blockIdx.x] = sdata[0];
}
template <class vobj, class Iterator>
__global__ void reduceKernel(const LatticeView<vobj> lat, typename vobj::scalar_object *buffer, Iterator n) {
typedef typename vobj::scalar_object sobj;
template <class vobj, class sobj,class Iterator>
__global__ void reduceKernel(const vobj *lat, sobj *buffer, Iterator n) {
Iterator blockSize = blockDim.x;
@ -179,32 +179,26 @@ __global__ void reduceKernel(const LatticeView<vobj> lat, typename vobj::scalar_
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////////////
// Possibly promote to double and sum
/////////////////////////////////////////////////////////////////////////////////////////////////////////
template <class vobj>
inline typename vobj::scalar_object sum_gpu(const Lattice<vobj> &lat)
inline typename vobj::scalar_objectD sumD_gpu(const vobj *lat, Integer osites)
{
typedef typename vobj::scalar_objectD sobj;
typedef decltype(lat) Iterator;
LatticeView<vobj> lat_v = lat.View();
Integer nsimd= vobj::Nsimd();
Integer size = osites*nsimd;
typedef typename vobj::scalar_object sobj;
typedef decltype(lat_v.begin()) Iterator;
Iterator size = lat.Grid()->lSites();
Iterator numThreads, numBlocks;
Integer numThreads, numBlocks;
getNumBlocksAndThreads(size, sizeof(sobj), numThreads, numBlocks);
Iterator smemSize = numThreads * sizeof(sobj);
/*
std::cout << GridLogDebug << "Starting reduction with:" << std::endl;
std::cout << GridLogDebug << "\tsize = " << size << std::endl;
std::cout << GridLogDebug << "\tnumThreads = " << numThreads << std::endl;
std::cout << GridLogDebug << "\tnumBlocks = " << numBlocks << std::endl;
std::cout << GridLogDebug << "\tsmemSize = " << smemSize << std::endl;
*/
Integer smemSize = numThreads * sizeof(sobj);
Vector<sobj> buffer(numBlocks);
sobj *buffer_v = &buffer[0];
reduceKernel<<< numBlocks, numThreads, smemSize >>>(lat_v, buffer_v, size);
reduceKernel<<< numBlocks, numThreads, smemSize >>>(lat, buffer_v, size);
cudaDeviceSynchronize();
cudaError err = cudaGetLastError();
@ -212,10 +206,21 @@ inline typename vobj::scalar_object sum_gpu(const Lattice<vobj> &lat)
printf("Cuda error %s\n",cudaGetErrorString( err ));
exit(0);
}
auto result = buffer_v[0];
lat.Grid()->GlobalSum(result);
return result;
}
/////////////////////////////////////////////////////////////////////////////////////////////////////////
// Return as same precision as input performing reduction in double precision though
/////////////////////////////////////////////////////////////////////////////////////////////////////////
template <class vobj>
inline typename vobj::scalar_object sum_gpu(const vobj *lat, Integer osites)
{
typedef typename vobj::scalar_object sobj;
sobj result;
result = sumD_gpu(lat,osites);
return result;
}
NAMESPACE_END(Grid);