mirror of
https://github.com/paboyle/Grid.git
synced 2024-11-10 07:55:35 +00:00
Merge branch 'feature/distil' of github.com:mmphys/Grid into feature/distil
This commit is contained in:
ferben
commit
3f2fe5c7e7
@ -3,6 +3,7 @@
|
||||
|
||||
#include <stack>
|
||||
#include <string>
|
||||
#include <list>
|
||||
#include <vector>
|
||||
#include <H5Cpp.h>
|
||||
#include <Grid/tensors/Tensors.h>
|
||||
@ -105,18 +106,17 @@ namespace Grid
|
||||
template <>
|
||||
void Hdf5Writer::writeDefault(const std::string &s, const std::string &x);
|
||||
|
||||
static hsize_t alignup(hsize_t n)
|
||||
{
|
||||
n--; // 1000 0011 --> 1000 0010
|
||||
n |= n >> 1; // 1000 0010 | 0100 0001 = 1100 0011
|
||||
n |= n >> 2; // 1100 0011 | 0011 0000 = 1111 0011
|
||||
n |= n >> 4; // 1111 0011 | 0000 1111 = 1111 1111
|
||||
n |= n >> 8; // ... (At this point all bits are 1, so further bitwise-or
|
||||
n |= n >> 16; // operations produce no effect.)
|
||||
n++; // 1111 1111 --> 1 0000 0000
|
||||
return n;
|
||||
class SortNode {
|
||||
public:
|
||||
int index;
|
||||
hsize_t dimsize;
|
||||
//bool operator<(const SortNode &r) { return dimsize < r.dimsize || (dimsize == r.dimsize && index < r.index); }
|
||||
//SortNode() = default;
|
||||
SortNode(int Index, hsize_t DimSize) : index{Index}, dimsize{DimSize} {}
|
||||
};
|
||||
|
||||
bool operator<(const SortNode &l, const SortNode &r) { return l.dimsize < r.dimsize || (l.dimsize == r.dimsize && l.index < r.index); }
|
||||
|
||||
template <typename U>
|
||||
void Hdf5Writer::writeMultiDim(const std::string &s, const std::vector<size_t> & Dimensions, const U * pDataRowMajor, size_t NumElements)
|
||||
{
|
||||
@ -125,30 +125,64 @@ namespace Grid
|
||||
std::vector<hsize_t> dim(rank);
|
||||
for(int i = 0; i < rank; i++)
|
||||
dim[i] = Dimensions[i];
|
||||
// write to file
|
||||
// write the entire dataset to file
|
||||
H5NS::DataSpace dataSpace(rank, dim.data());
|
||||
|
||||
size_t DataSize = NumElements * sizeof(U);
|
||||
if (DataSize > dataSetThres_)
|
||||
{
|
||||
// Make sure the chunk size is < 4GB
|
||||
// First few prime numbers from https://oeis.org/A000040
|
||||
static const unsigned short Primes[] = { 2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31,
|
||||
37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 101, 103, 107, 109,
|
||||
113, 127, 131, 137, 139, 149, 151, 157, 163, 167, 173, 179, 181, 191, 193,
|
||||
197, 199, 211, 223, 227, 229, 233, 239, 241, 251, 257, 263, 269, 271 };
|
||||
constexpr int NumPrimes = sizeof( Primes ) / sizeof( Primes[0] );
|
||||
// Make sure 1) each dimension; and 2) chunk size is < 4GB
|
||||
const hsize_t MaxElements = ( sizeof( U ) == 1 ) ? 0xffffffff : 0x100000000 / sizeof( U );
|
||||
hsize_t ElementsPerChunk = 1;
|
||||
bool bTooBig = false;
|
||||
for( unsigned int i = rank - 1; i != -1; i-- ) {
|
||||
for( int i = rank - 1 ; i != -1 ; i-- ) {
|
||||
auto &d = dim[i];
|
||||
if( bTooBig )
|
||||
// Chunk size is already as big as can be - remaining dimensions = 1
|
||||
dim[i] = 1;
|
||||
d = 1; // Chunk size is already as big as can be - remaining dimensions = 1
|
||||
else {
|
||||
// If individual dimension too big, reduce by prime factors if possible
|
||||
for( int PrimeIdx = 0; d > MaxElements && PrimeIdx < NumPrimes; ) {
|
||||
if( d % Primes[PrimeIdx] )
|
||||
PrimeIdx++;
|
||||
else
|
||||
d /= Primes[PrimeIdx];
|
||||
}
|
||||
const char ErrorMsg[] = " dimension > 4GB without small prime factors. "
|
||||
"Hdf5IO chunk size will be inefficient.";
|
||||
if( d > MaxElements ) {
|
||||
std::cout << GridLogMessage << "Individual" << ErrorMsg << std::endl;
|
||||
hsize_t quotient = d / MaxElements;
|
||||
if( d % MaxElements )
|
||||
quotient++;
|
||||
d /= quotient;
|
||||
}
|
||||
// Now make sure overall size is not too big
|
||||
ElementsPerChunk *= dim[i];
|
||||
if( ElementsPerChunk >= MaxElements ) {
|
||||
hsize_t OverflowCheck = ElementsPerChunk;
|
||||
ElementsPerChunk *= d;
|
||||
assert( OverflowCheck == ElementsPerChunk / d && "Product of dimensions overflowed hsize_t" );
|
||||
// If product of dimensions too big, reduce by prime factors
|
||||
for( int PrimeIdx = 0; ElementsPerChunk > MaxElements && PrimeIdx < NumPrimes; ) {
|
||||
bTooBig = true;
|
||||
hsize_t dividend = ElementsPerChunk / MaxElements;
|
||||
hsize_t remainder = ElementsPerChunk % MaxElements;
|
||||
if( remainder )
|
||||
dividend++;
|
||||
dim[i] = dim[i] / dividend;
|
||||
if( d % Primes[PrimeIdx] )
|
||||
PrimeIdx++;
|
||||
else {
|
||||
d /= Primes[PrimeIdx];
|
||||
ElementsPerChunk /= Primes[PrimeIdx];
|
||||
}
|
||||
}
|
||||
if( ElementsPerChunk > MaxElements ) {
|
||||
std::cout << GridLogMessage << "Product of" << ErrorMsg << std::endl;
|
||||
hsize_t quotient = ElementsPerChunk / MaxElements;
|
||||
if( ElementsPerChunk % MaxElements )
|
||||
quotient++;
|
||||
d /= quotient;
|
||||
ElementsPerChunk /= quotient;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -114,7 +114,7 @@ typedef Eigen::TensorFixedSize<TestScalar, Eigen::Sizes<9,4,2>, Eigen::StorageOp
|
||||
typedef std::vector<Tensor_9_4_2> aTensor_9_4_2;
|
||||
typedef Eigen::TensorFixedSize<SpinColourVector, Eigen::Sizes<6,5>> LSCTensor;
|
||||
#ifdef DEBUG
|
||||
typedef Eigen::TensorFixedSize<iMatrix<iVector<iMatrix<iVector<LorentzColourMatrix,5>,2>,7>,3>, Eigen::Sizes<2,2,11,10,9>, Eigen::StorageOptions::RowMajor> LCMTensor;
|
||||
typedef Eigen::TensorFixedSize<iMatrix<iVector<iMatrix<iVector<LorentzColourMatrix,5>,2>,7>,3>, Eigen::Sizes<2,4,11,10,9>, Eigen::StorageOptions::RowMajor> LCMTensor;
|
||||
#endif
|
||||
|
||||
class PerambIOTestClass: Serializable {
|
||||
@ -132,9 +132,6 @@ public:
|
||||
, Tensor_9_4_2, tensor_9_4_2
|
||||
, aTensor_9_4_2, atensor_9_4_2
|
||||
, LSCTensor, MyLSCTensor
|
||||
#ifdef DEBUG
|
||||
, LCMTensor, MyLCMTensor
|
||||
#endif
|
||||
);
|
||||
PerambIOTestClass()
|
||||
: DistilParameterNames {"alpha", "beta", "gamma", "delta", "epsilon", "zeta"}
|
||||
@ -153,23 +150,19 @@ public:
|
||||
for( auto &t : atensor_9_4_2 )
|
||||
SequentialInit(t, Flag);
|
||||
SequentialInit( MyLSCTensor );
|
||||
#ifdef DEBUG
|
||||
SequentialInit( MyLCMTensor );
|
||||
#endif
|
||||
}
|
||||
};
|
||||
|
||||
#define RDR_ Hdf5Reader
|
||||
#define WTR_ Hdf5Writer
|
||||
#define TensorWriteReadInnerNoInit( T ) \
|
||||
filename = "iotest_" + std::to_string(++TestNum) + "_" #T ".h5"; \
|
||||
filename = "iotest_" + std::to_string(++TestNum) + "_" #T + pszExtension; \
|
||||
ioTest<WTR_, RDR_, T>(filename, t, #T, #T);
|
||||
#define TensorWriteReadInner( T ) SequentialInit( t ); TensorWriteReadInnerNoInit( T )
|
||||
#define TensorWriteRead( T ) { T t ; TensorWriteReadInner( T ) }
|
||||
#define TensorWriteReadV(T, ... ) { T t( __VA_ARGS__ ); TensorWriteReadInner( T ) }
|
||||
#define TensorWriteReadLarge( T ) { std::unique_ptr<T> p{new T}; T &t{*p}; TensorWriteReadInnerNoInit(T) }
|
||||
|
||||
void EigenHdf5IOTest(void)
|
||||
template <typename WTR_, typename RDR_>
|
||||
void EigenHdf5IOTest(const char * pszExtension)
|
||||
{
|
||||
unsigned int TestNum = 0;
|
||||
std::string filename;
|
||||
@ -300,8 +293,10 @@ int main(int argc,char **argv)
|
||||
ioTest<Hdf5Writer, Hdf5Reader>("iotest.h5", obj, "HDF5 (object) ");
|
||||
ioTest<Hdf5Writer, Hdf5Reader>("iotest.h5", vec, "HDF5 (vector of objects)");
|
||||
std::cout << "\n==== detailed Hdf5 tensor tests (Grid::EigenIO)" << std::endl;
|
||||
EigenHdf5IOTest();
|
||||
EigenHdf5IOTest<Hdf5Writer, Hdf5Reader>(".h5");
|
||||
#endif
|
||||
std::cout << "\n==== detailed binary tensor tests (Grid::EigenIO)" << std::endl;
|
||||
EigenHdf5IOTest<BinaryWriter, BinaryReader>(".bin");
|
||||
|
||||
std::cout << "\n==== vector flattening/reconstruction" << std::endl;
|
||||
typedef std::vector<std::vector<std::vector<double>>> vec3d;
|
||||
|
||||
Loading…
Reference in New Issue
Block a user