Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on uniform random number generation
A parallel iterative linear system solver with dynamic load balancing
ICS '98 Proceedings of the 12th international conference on Supercomputing
Asynchronous Iterative Methods for Multiprocessors
Journal of the ACM (JACM)
Timing models and local stopping criteria for asynchronous iterative algorithms
Journal of Parallel and Distributed Computing
Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers (2nd Edition)
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This paper presents design and experimental results of a parallel linear equation solver by asynchronous partial Gauss-Seidel method. The basic idea of this method is derived from the asynchronous iterative method; newly computed values of unknowns are broadcast to all other processors and are incorporated into computing the next value immediately after they are received. However, since the asynchronous iterative method requires frequent data passing, it is difficult to achieve high performance on practical cluster computing systems due to its enormous communication overhead. To avoid it, the asynchronous partial Gauss-Seidel method reduces frequency of broadcasting new values of unknowns by passing multiple values in a chunk. The experimental results show the advantage of the asynchronous partial Gauss-Seidel method.