Title :
The IBiCGStab method on bulk synchronous parallel architectures
Author :
Yang, Laurence Tianruo ; Shaw, Ruth E.
Author_Institution :
Dept. of Comput. Sci., Saint Francis Xavier Univ., Antigonish, NS, Canada
Abstract :
In this paper, an improved version of the BiCGStab method for the solutions of large and sparse linear systems of equations with unsymmetric coefficient matrices is proposed. The method combines elements of numerical stability and parallel algorithm design without increasing the computational costs. The algorithm is derived such that all inner products of a single iteration step are independent and communication time required for inner product can be overlapped efficiently with computation time of vector updates. Therefore, the cost of global communication can be significantly reduced. In this paper, the bulk synchronous parallel (BSP) model is used to design a fully efficient, scalable and portable parallel proposed algorithm and to provide accurate performance prediction of the algorithm for a wide range of architectures including the Cray T3D, the Parsytec, and a cluster of workstations connected by an Ethernet. This performance model provides us useful insight in the time complexity of the method using only a few system dependent parameters based on a simple and accurate cost modelling. The theoretical performance prediction are compared with some preliminary measured timing results of a numerical application from ocean flow simulation.
Keywords :
computational complexity; geophysics computing; gradient methods; iterative methods; mathematics computing; parallel algorithms; parallel architectures; synchronisation; BiCGStab method; Cray T3D; Ethernet; Parsytec; bulk synchronous parallel architectures; iterative methods; linear systems; numerical computing; ocean flow simulation; parallel algorithm; time complexity; unsymmetric coefficient matrices; Algorithm design and analysis; Clustering algorithms; Costs; Equations; Linear systems; Numerical stability; Parallel algorithms; Parallel architectures; Predictive models; Sparse matrices;
Conference_Titel :
High Performance Computing Systems and Applications, 2002. Proceedings. 16th Annual International Symposium on
Print_ISBN :
0-7695-1626-2
DOI :
10.1109/HPCSA.2002.1019147