reentrant TA::rand()
#394
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reentrant TA::rand()
#394
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copied https://github.com/ValeevGroup/mpqc4/blob/6714a216d963f8252b7be0d379a57e7c9fa0b732/src/mpqc/util/misc/thread_specific.h and https://github.com/ValeevGroup/mpqc4/blob/530f8d01cd84702ec5b387f7658741c80eaeca0a/src/mpqc/util/misc/pool.h to TiledArray/util/thread_specific.h and fixed to be properly movable
- TA::{rand,drand} are reentrant versions of rand and drand48 that uses Boost.Random's mt19937 and uniform distribution classes (the latter is needed to produce platform-portable results, see https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2020/p2059r0.pdf ) ... TA::srand controls the seeds of the thread-specific random engines
- MakeRandom now uses TA::rand instead of std::rand ... the latter is not reentrant so technically any use of DistArray::fill_random was UB ... single-threaded version of DistArray::fill_random to get random tensors witrh contents independent of schedule will be introduced in a separate commit
…les,fill_random} default is to use MADWorld's taskq, but useful with non-reentrant ops or, even when op is reentrant, e.g. to ensure that same random tensor is generated by DistArray::fill_random (since initial state of every thread-specific random engine is the same tiles generated by different threads will initially have the same content ... )
… hand-rolled equivalent
…ordinal()} assert batch_size=1
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introduces
TA::{rand,drand,srand}TA::{rand,drand}are reentrant versions ofrandanddrand48that usesBoost.Random's mt19937 and uniform distribution classes (the latter is needed to produce platform-portable results, see https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2020/p2059r0.pdf ) ...TA::srandcontrols the seeds of the thread-specific random enginesdetail::MakeRandomnow usesTA::randinstead ofstd::rand(the latter is not guaranteed to be reentrant.DistArray::{init_elements,init_tiles,fill_random}so that it is possible to useDistArray::fill_randomto get reproducibly-random tensors even if using >1 thread/rank.