suport for data preserving in NRVec::resize
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74835e5264
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5480de6ff2
@ -81,6 +81,10 @@ template<typename C> class NRSMat_from1;
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template<typename C> class SparseMat;
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template<typename C> class SparseSMat;
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template<typename C> class CSRMat;
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template<typename C> class NRPerm;
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template<typename C> class CyclePerm;
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template<typename C> class Partition;
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template<typename C> class CompressedPartition;
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//trick to allow real and imag part of complex as l-values
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template<typename T>
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@ -375,6 +379,11 @@ generate_traits(NRVec_from1)
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generate_traits(SparseMat)
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generate_traits(SparseSMat) //product leading to non-symmetric result not implemented
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generate_traits(CSRMat)
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generate_traits(NRPerm)
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generate_traits(CyclePerm)
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generate_traits(Partition)
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generate_traits(CompressedPartition)
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#undef generate_traits
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4
t.cc
4
t.cc
@ -2146,7 +2146,7 @@ int tot=p.generate_all_lex(printme);
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cout <<"generated "<<tot<<endl;
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}
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if(0)
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if(1)
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{
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int n;
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cin >>n >>unitary_n;
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@ -2158,7 +2158,7 @@ if(tot!=partitions(n)) laerror("internal error in partition generation or enumer
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if(space_dim!=longpow(unitary_n,n)) {cout<<space_dim<<" "<<ipow(unitary_n,n)<<endl;laerror("integer overflow or internal error in space dimensions");}
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}
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if(1)
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if(0)
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{
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int n;
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cin >>n ;
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85
vec.h
85
vec.h
@ -299,8 +299,8 @@ public:
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//! determine the number of elements
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inline int size() const;
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//! resize the current vector
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void resize(const int n);
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//! resize the current vector, optionally preserving data
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void resize(const int n, const bool preserve=false);
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//!deallocate the current vector
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void dealloc(void) {resize(0);}
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@ -965,14 +965,25 @@ NRVec<T> & NRVec<T>::operator=(const NRVec<T> &rhs) {
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* @param[in] n requested size
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******************************************************************************/
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template <typename T>
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void NRVec<T>::resize(const int n) {
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void NRVec<T>::resize(const int n, const bool preserve)
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{
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#ifdef DEBUG
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if(n < 0) laerror("illegal dimension");
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if(n < 0) laerror("illegal dimension in NRVec::resize");
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#endif
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if(count){
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if(n == 0){
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if(--(*count) <= 0){
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if(v){
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if(preserve && n<nn) laerror("cannot resize to smaller vector and preserve data");
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T *vold=0;
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int nnold=0;
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bool preserved=false;
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bool do_delete=false;
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if(count) //we are allocated
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{
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if(n == 0) //just deallocate
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{
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if(--(*count) <= 0)
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{
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if(v)
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{
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#ifdef CUDALA
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if(location == cpu){
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#endif
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@ -990,14 +1001,19 @@ void NRVec<T>::resize(const int n) {
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v = 0;
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return;
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}
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if(*count > 1) {
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if(*count > 1) //detach from shared data
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{
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(*count)--;
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count = 0;
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vold=v;
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v = 0;
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nnold=nn;
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nn = 0;
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preserved=true;
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}
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}
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if(!count){
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if(!count) //we were not allocated or we just detached
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{
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count = new int;
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*count = 1;
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nn = n;
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@ -1009,25 +1025,58 @@ void NRVec<T>::resize(const int n) {
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else
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v = (T*) gpualloc(nn*sizeof(T));
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#endif
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if(preserved && preserve) goto do_preserve;
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return;
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}
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// *count = 1 in this branch
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if (n != nn) {
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// *count == 1 in this branch
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if (n == nn) return; //nothing to do
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nnold=nn;
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nn = n;
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#ifdef CUDALA
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if(location == cpu){
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if(location == cpu)
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{
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#endif
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delete[] v;
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if(preserve) {vold=v; do_delete=true;} else delete[] v;
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v = new T[nn];
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#ifdef CUDALA
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}else{
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gpufree(v);
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}
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else
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{
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if(preserve) {vold=v; do_delete=true;} else gpufree(v);
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v = (T*) gpualloc(nn*sizeof(T));
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}
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#endif
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if(!preserve) return;
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//copy data from old location and zero excess allocated memory
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do_preserve:
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if(!preserve || !preserved) laerror("assertion failed in NRVec::resize");
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// omit this check since we would need to have traits for presently unknown user defined classes
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// if(!LA_traits<T>::is_plaindata()) laerror("do not know how to preserve non-plain data");
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if(nnold>=nn) laerror("assertion2 failed in NRVec::resize");
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#ifdef CUDALA
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if(location == cpu)
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{
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#endif
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for(int i=0; i<nnold; ++i) v[i]=vold[i]; //preserve even non-plain data classes
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memset(v+nnold,0,(nn-nnold)*sizeof(T)); //just zero the new memory
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if(do_delete) delete[] vold;
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#ifdef CUDALA
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}
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else
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{
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//!!!works only with plain data
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cublasSetVector(nnold, sizeof(T), vold, 1, v, 1);
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TEST_CUBLAS("cublasSetVector");
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T a(0);
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smart_gpu_set(nn-nnold, a, v+nnold);
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if(do_delete) gpufree(vold);
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}
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#endif
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return;
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}
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