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Faster reductions, important on single node staggered
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@ -244,19 +244,11 @@ namespace Grid {
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template<class sobj,class vobj> strong_inline
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RealD axpy_norm(Lattice<vobj> &ret,sobj a,const Lattice<vobj> &x,const Lattice<vobj> &y){
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ret.checkerboard = x.checkerboard;
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conformable(ret,x);
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conformable(x,y);
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axpy(ret,a,x,y);
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return norm2(ret);
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return axpy_norm_fast(ret,a,x,y);
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}
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template<class sobj,class vobj> strong_inline
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RealD axpby_norm(Lattice<vobj> &ret,sobj a,sobj b,const Lattice<vobj> &x,const Lattice<vobj> &y){
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ret.checkerboard = x.checkerboard;
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conformable(ret,x);
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conformable(x,y);
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axpby(ret,a,b,x,y);
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return norm2(ret); // FIXME implement parallel norm in ss loop
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return axpby_norm_fast(ret,a,b,x,y);
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}
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}
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@ -33,7 +33,7 @@ namespace Grid {
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// Deterministic Reduction operations
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////////////////////////////////////////////////////////////////////////////////////////////////////
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template<class vobj> inline RealD norm2(const Lattice<vobj> &arg){
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ComplexD nrm = innerProduct(arg,arg);
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auto nrm = innerProduct(arg,arg);
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return std::real(nrm);
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}
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@ -43,12 +43,12 @@ inline ComplexD innerProduct(const Lattice<vobj> &left,const Lattice<vobj> &righ
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{
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typedef typename vobj::scalar_type scalar_type;
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typedef typename vobj::vector_typeD vector_type;
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scalar_type nrm;
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GridBase *grid = left._grid;
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std::vector<vector_type,alignedAllocator<vector_type> > sumarray(grid->SumArraySize());
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const int pad = 8;
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scalar_type nrm;
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std::vector<scalar_type,alignedAllocator<vector_type> > sumarray(grid->SumArraySize()*pad);
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parallel_for(int thr=0;thr<grid->SumArraySize();thr++){
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int nwork, mywork, myoff;
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GridThread::GetWork(left._grid->oSites(),thr,mywork,myoff);
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@ -57,17 +57,69 @@ inline ComplexD innerProduct(const Lattice<vobj> &left,const Lattice<vobj> &righ
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for(int ss=myoff;ss<mywork+myoff; ss++){
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vnrm = vnrm + innerProductD(left._odata[ss],right._odata[ss]);
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}
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sumarray[thr]=TensorRemove(vnrm) ;
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// All threads sum across SIMD; reduce serial work at end
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// one write per cacheline with streaming store
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vstream(sumarray[thr*pad],Reduce(TensorRemove(vnrm))) ;
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}
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vector_type vvnrm; vvnrm=zero; // sum across threads
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nrm=0.0;
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for(int i=0;i<grid->SumArraySize();i++){
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vvnrm = vvnrm+sumarray[i];
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nrm = nrm+sumarray[i*pad];
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}
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nrm = Reduce(vvnrm);// sum across simd
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right._grid->GlobalSum(nrm);
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return nrm;
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}
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/////////////////////////
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// Fast axpby_norm
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// z = a x + b y
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// return norm z
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/////////////////////////
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template<class sobj,class vobj> strong_inline RealD
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axpy_norm_fast(Lattice<vobj> &z,sobj a,const Lattice<vobj> &x,const Lattice<vobj> &y)
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{
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sobj one(1.0);
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return axpby_norm_fast(z,a,one,x,y);
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}
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template<class sobj,class vobj> strong_inline RealD
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axpby_norm_fast(Lattice<vobj> &z,sobj a,sobj b,const Lattice<vobj> &x,const Lattice<vobj> &y)
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{
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const int pad = 8;
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z.checkerboard = x.checkerboard;
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conformable(z,x);
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conformable(x,y);
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typedef typename vobj::scalar_type scalar_type;
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typedef typename vobj::vector_typeD vector_type;
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RealD nrm;
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GridBase *grid = x._grid;
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Vector<RealD> sumarray(grid->SumArraySize()*pad);
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parallel_for(int thr=0;thr<grid->SumArraySize();thr++){
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int nwork, mywork, myoff;
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GridThread::GetWork(x._grid->oSites(),thr,mywork,myoff);
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// private to thread; sub summation
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decltype(innerProductD(z._odata[0],z._odata[0])) vnrm=zero;
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for(int ss=myoff;ss<mywork+myoff; ss++){
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vobj tmp = a*x._odata[ss]+b*y._odata[ss];
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vnrm = vnrm + innerProductD(tmp,tmp);
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vstream(z._odata[ss],tmp);
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}
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vstream(sumarray[thr*pad],real(Reduce(TensorRemove(vnrm)))) ;
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}
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nrm = 0.0; // sum across threads; linear in thread count but fast
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for(int i=0;i<grid->SumArraySize();i++){
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nrm = nrm+sumarray[i*pad];
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}
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z._grid->GlobalSum(nrm);
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return nrm;
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}
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template<class Op,class T1>
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inline auto sum(const LatticeUnaryExpression<Op,T1> & expr)
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