A Supernodal Cholesky Factorization Algorithm for Shared-Memory Multiprocessors

Authors:
  • ENEsmond Ng
    Esmond Ng
  • BPBarry W. Peyton
    Barry W. Peyton
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Abstract
This paper presents a parallel sparse Cholesky factorization algorithm for shared-memory MIMD multiprocessors. The algorithm is particularly well suited for vector supercomputers with multiple processors, such as the Cray Y-MP. The new algorithm is a straightforward parallelization of the left-looking supernodal sparse Cholesky factorization algorithm. Like its sequential predecessor, it improves performance by reducing indirect addressing and memory traffic. Experimental results on a Cray Y-MP demonstrate the effectiveness of the new algorithm. On eight processors of a Cray Y-MP, the new routine performs the factorization at rates exceeding one Gflop for several test problems from the Harwell–Boeing sparse matrix collection.

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