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<p><b>Abstract</b>—Hierarchically organized ensembles of shared memory multiprocessors possess a richer and more complex model of locality than previous generation multicomputers with single processor nodes. These <it>dual-tier computers</it> introduce many new factors into the programmer's performance model. We present a methodology for implementing block-structured numerical applications on dual-tier computers and a run-time infrastructure, called KeLP2, that implements the methodology. KeLP2 supports two levels of locality and parallelism via hierarchical SPMD control flow, run-time geometric meta-data, and asynchronous collective communication. KeLP applications can effectively overlap communication with computation under conditions where nonblocking point-to-point message passing fails to do so. KeLP's abstractions hide considerable detail without sacrificing performance and dual-tier applications written in KeLP consistently outperform equivalent single-tier implementations written in MPI. We describe the KeLP2 model and show how it facilitates the implementation of five block-structured applications specially formulated to hide communication latency on dual-tiered architectures. We support our arguments with empirical data from applications running on various single- and dual-tier multicomputers. KeLP2 supports a migration path from single-tier to dual-tier platforms and we illustrate this capability with a detailed programming example.</p>
Dual-tier parallel computers, hierarchical parallelism, KeLP, block-structured scientific applications, scientific application requirements, C++ framework, SMP clusters.

S. J. Fink and S. B. Baden, "A Programming Methodology for Dual-Tier Multicomputers," in IEEE Transactions on Software Engineering, vol. 26, no. , pp. 212-226, 2000.
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