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Triangular solves are a core task of many more advanced matrix algorithms. We want to implement.
A simple serial triangular solve.
A multithreaded triangular solve using a threadpool.
The multithreaded version also requires serial triangular solves. So it is natural that both needs to be done.
A precondition for this issue is a decision on the parallelization framework in #11 .
The text was updated successfully, but these errors were encountered:
Sounds good. My goal for Householder is that eventually we have modern task based algorithms for all decompositions. For LDL^T see for example (https://hal.inria.fr/hal-00809663/document). However,
we still want single core algorithms as well (lots of applications where you want to do small decompositions within a thread and not have your linear algebra spread out of all threads)
Also for parallel algorithms we usually need to single core versions as components.
Triangular solves are a core task of many more advanced matrix algorithms. We want to implement.
The multithreaded version also requires serial triangular solves. So it is natural that both needs to be done.
A precondition for this issue is a decision on the parallelization framework in #11 .
The text was updated successfully, but these errors were encountered: