Abstract
The bulk synchronous parallel (BSP) model promises scalable and portable software for a wide range of applications. A BSP computer consists of several processors, each with private memory, and a communication network that delivers access to remote memory in uniform time.Numerical linear algebra computations can benefit from the BSP model, both in terms of simplicity and efficiency. Dense LU decomposition and other computations can be made more efficient by using the new technique of two-phase randomised broadcasting, which is motivated by a cost analysis in the BSP model. For LU decomposition with partial pivoting, this technique reduces the communication time by a factor of (√p+1)/3, where p is the number of processors.Theoretical analysis, together with benchmark values for machine parameters, can be used to predict execution time. Such predictions are verified by numerical experiments on a 64-processor Cray T3D. The experimental results confirm the advantage of two-phase randomised broadcasting.KeywordsGrid DistributionNumerical Linear AlgebraData WordProgram TextPartial PivotingThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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