APRIL: A Processor Architecture for Multiprocessing

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APRIL: A Processor Architecture for Multiprocessing (1990)

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by Anant Agarwal , Beng-Hong Lim , David Kranz , John Kubiatowicz

Venue:	IN PROCEEDINGS OF THE 17TH ANNUAL INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE
Citations:	283 - 25 self

BibTeX

@INPROCEEDINGS{Agarwal90april:a,
    author = {Anant Agarwal and Beng-Hong Lim and David Kranz and John Kubiatowicz},
    title = {APRIL: A Processor Architecture for Multiprocessing},
    booktitle = {IN PROCEEDINGS OF THE 17TH ANNUAL INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE},
    year = {1990},
    pages = {104--114},
    publisher = {}
}

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Abstract

Processors in large-scale multiprocessors must be able to tolerate large communication latencies and synchronization delays. This paper describes the architecture of a rapid-context-switching processor called APRIL with support for fine-grain threads and synchronization. APRIL achieves high single-thread performance and supports virtual dynamic threads. A commercial RISC-based implementation of APRIL and a run-time software system that can switch contexts in about 10 cycles is described. Measurements taken for several parallel applications on an APRIL simulator show that the overhead for supporting parallel tasks based on futures is reduced by a factor of twoover a corresponding implementation on the Encore Multimax. The scalability of a multiprocessor based on APRIL is explored using a performance model. We show that the SPARC-based implementation of APRIL can achieve close to 80# processor utilization with as few as three resident threads per processor in a large-scale cache-based machine with an average base network latency of 55 cycles.

Keyphrases

processor architecture rapid-context-switching processor support virtual dynamic thread average base network latency commercial risc-based implementation parallel task high single-thread performance synchronization delay corresponding implementation resident thread large-scale cache-based machine april simulator show fine-grain thread large communication latency processor utilization large-scale multiprocessor encore multimax performance model sparc-based implementation run-time software system several parallel application

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