Abstract. Static symbolic factorization coupled with supernode partitioning and asynchronous computation scheduling can achieve high gigaflop rates for parallel sparse LU factorization with partial pivoting. This paper studies properties of elimination forests and uses them to optimize supernode partitioning/amalgamation and execution scheduling. It also proposes supernodal matrix multiplication to speed up kernel computation by retaining the BLAS-3 level efficiency and avoiding unnecessary arithmetic operations. The experiments show that our new design with proper space optimization, called S +, improves our previous solution substantially and can achieve up to 10 GFLOPS on 128 Cray T3E 450MHz nodes. Key words. Gaussian elimination with partial pivoting, LU factorization, sparse matrices, elimination forests, supernode amalgamation and partitioning, asynchronous computation scheduling AMS subject classifications. 65F50, 65F05 PII. S089547989833738
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