Sparse Cholesky factorization on a local-memory multiprocessor

Technical Report · Mon Mar 31 23:00:00 EST 1986

DOI:https://doi.org/10.2172/5868908· OSTI ID:5868908

George, A.; Heath, M. T.; Liu, J.; Ng, E.

The problem of factoring a large sparse positive definite matrix is implemented on a multiprocessor system. The processors are assumed to have substantial local memory but no globally shared memory. They communicate among themselves and with a host processor through message passing. The primary interest is in designing an algorithm which exploits parallelism, rather than in exploiting features of the underlying topology of the hardware. However, part of the study is aimed at determining, for certain sparse matrix problems, whether hardware based on the binary hypercube topology adequately supports the communication requirements for such problems. Numerical results from experiments running on a multiprocessor simulator are included. 20 refs., 7 figs., 5 tabs.

• Research Organization: Oak Ridge National Lab., TN (USA)
• DOE Contract Number: AC05-84OR21400
• OSTI ID: 5868908
• Report Number(s): ORNL/TM-9962; ON: DE86010082
• Country of Publication: United States
• Language: English

Related Subjects

658000 -- Mathematical Physics-- (-1987)
71 CLASSICAL AND QUANTUM MECHANICS
GENERAL PHYSICS
99 GENERAL AND MISCELLANEOUS
990200* -- Mathematics & Computers
ARRAY PROCESSORS
COMMUNICATIONS
DATA
DATA TRANSMISSION
DATA-FLOW PROCESSING
EXPERIMENTAL DATA
FACTORIZATION
INFORMATION
MATRICES
NUMERICAL DATA
PROGRAMMING