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@ -58,7 +58,7 @@ for(SPMatindex k=0; k<nn; ++k) //summation loop
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//make multiply via blas
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NRMat<T> prod=av.otimes(bv,false,alpha);
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//scatter the results
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//scatter the results -- probably the computational bottleneck
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for(i=0; i<prod.nrows(); ++i) for(j=0; j<prod.ncols(); ++j)
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add(ai[i],bi[j],prod(i,j),false);
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@ -85,10 +85,42 @@ return *this;
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}
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template <class T>
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void SparseSMat<T>::axpy(const T alpha, const SparseSMat &x, const bool transp)
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{
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if(nn!=x.nn) laerror("incompatible matrix dimensions in SparseSMat::axpy");
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if(alpha==(T)0) return;
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copyonwrite();
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for(SPMatindex i=0; i<nn; ++i) if(x.v[i])
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{
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if(!v[i]) v[i] = new std::map<SPMatindex,T>;
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typename std::map<SPMatindex,T>::iterator p;
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for(p=x.v[i]->begin(); p!=x.v[i]->end(); ++p) (*v[i])[p->first] = p->second * alpha;
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}
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}
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template <class T>
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void SparseSMat<T>::gemv(const T beta, NRVec<T> &r, const char trans, const T alpha, const NRVec<T> &x) const
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{
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if(nn!=r.size() || nn!= x.size()) laerror("incompatible matrix vector dimensions in SparseSMat::gemv");
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r *= beta;
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if(alpha == (T)0) return;
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r.copyonwrite();
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for(SPMatindex i=0; i<nn; ++i) if(v[i])
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{
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typename std::map<SPMatindex,T>::iterator p;
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for(p=v[i]->begin(); p!=v[i]->end(); ++p) r[i] += x[p->first] * p->second * alpha ;
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}
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}
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#define INSTANTIZE(T) \
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template void SparseSMat<T>::gemm(const T beta, const SparseSMat &a, const char transa, const SparseSMat &b, const char transb, const T alpha); \
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template SparseSMat<T> & SparseSMat<T>::operator*=(const T &a); \
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template void SparseSMat<T>::gemv(const T beta, NRVec<T> &r, const char trans, const T alpha, const NRVec<T> &x) const; \
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template void SparseSMat<T>::axpy(const T alpha, const SparseSMat &x, const bool transp); \
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INSTANTIZE(double)
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