PRAM programming: in theory and in practice

That the influence of the PRAM model is ubiquitous in parallel algorithm design is as clear as the fact that it is technologically infeasible for the forseeable future. The current generation of parallel hardware prominently features distributed memory and high-performance interconnection networks—very much the antithesis of the shared memory required for the PRAM model. It has been shown that, in spite of communication costs, for some problems very fast parallel algorithms are available for distributed-memory machines—from embarassingly parallel problems to sorting and numerical analysis. In contrast it is known that for other classes of problem PRAM-style shared-memory simulation on a distributed-memory machine can, in theory, produce solutions of comparable performance to the best possible for such architectures. The Bulk Synchronous Parallel (BSP) model accurately represents most parallel machines—theoretical and actual—in an execution and cost model. We introduce a scalable portable PRAM realization appropriate for BSP computers and a methodology for usage. Our system is fast and built upon the familiar sequential C++ coupled with the new standard BSP library of parallel computation and communication primitives. It is portable to and predictable on a vast number of parallel computers including workstation clusters, a 256-processor Cray T3D, an 8-node IBM SP/2 and a 4-node shared-memory SGI Power Challenge machine. Our approach achieves simplicity of programming over direct-mode BSP programming for reasonable overhead cost. We objectively compare optimized BSP and PRAM algorithms implemented with our C++ PRAM library and provide encouraging experimental results for our new style of programming. Copyright © 2000 John Wiley & Sons, Ltd.