Parallel solution of triangular systems on distributed-memory multiprocessors
SIAM Journal on Scientific and Statistical Computing
A new method for solving triangular systems on distributed-memory message-passing multiprocessors
SIAM Journal on Scientific and Statistical Computing
ScaLAPACK user's guide
The formal derivation of parallel triangular system solvers using a coordination-based design method
Parallel Computing - Special issue on coordination languages for parallel programming
Solving Linear Systems on Vector and Shared Memory Computers
Solving Linear Systems on Vector and Shared Memory Computers
Three algorithms for Cholesky factorization on distributed memory using packed storage
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
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The aim is to present a new data distribution of triangular matrices that provides steady distribution of blocks among processes and reduces memory wasting compared to the standard block-cyclic data layout used in the ScaLAPACK library for dense matrix computations. A new algorithm for solving triangular systems of linear equations is also introduced. The results of experiments performed on a cluster of Itanium 2 processors and Cray X1 show that in some cases, the new method is faster than corresponding PBLAS routines PSTRSV and PSTRSM.