SCMP: A Single-Chip Message-Passing Parallel Computer

Baker, J.M.; Gold, Brian T.; Bucciero, Mark; Bennett, Sidney; Mahajan, Rajneesh; Ramachandran, Priyadarshini; Shah, Jignesh

doi:10.1023/b:supe.0000040612.33760.8a

Cited by 3 publications

(1 citation statement)

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“…The intermediate conclusion in this work is that shared memory is the best approach for programming these systems, but we argue that message passing is a competitive and important model in practice. Furthermore, MPI programs are usually a set of cooperating processes, while OpenMP programs are typically threads-processes that share address spaces [6][7][8]. For consistency, we refer to both MPI processes and OpenMP threads as threads of the program.…”

Section: Assumptions and Definitionsmentioning

confidence: 99%

Effective On-Chip Communication for Message Passing Programs on Multi-Core Processors

Huh

Lee

2021

Electronics

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Shared memory is the most popular parallel programming model for multi-core processors, while message passing is generally used for large distributed machines. However, as the number of cores on a chip increases, the relative merits of shared memory versus message passing change, and we argue that message passing becomes a viable, high performing, and parallel programming model. To demonstrate this hypothesis, we compare a shared memory architecture with a new message passing architecture on a suite of applications tuned for each system independently. Perhaps surprisingly, the fundamental behaviors of the applications studied in this work, when optimized for both models, are very similar to each other, and both could execute efficiently on multicore architectures despite many implementations being different from each other. Furthermore, if hardware is tuned to support message passing by supporting bulk message transfer and the elimination of unnecessary coherence overheads, and if effective support is available for global operations, then some applications would perform much better on a message passing architecture. Leveraging our insights, we design a message passing architecture that supports both memory-to-memory and cache-to-cache messaging in hardware. With the new architecture, message passing is able to outperform its shared memory counterparts on many of the applications due to the unique advantages of the message passing hardware as compared to cache coherence. In the best case, message passing achieves up to a 34% increase in speed over its shared memory counterpart, and it achieves an average 10% increase in speed. In the worst case, message passing is slowed down in two applications—CG (conjugate gradient) and FT (Fourier transform)—because it could not perform well on the unique data sharing patterns as its counterpart of shared memory. Overall, our analysis demonstrates the importance of considering message passing as a high performing and hardware-supported programming model on future multicore architectures.

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Section: Assumptions and Definitionsmentioning

confidence: 99%