Exploiting application tunability for efficient, predictable parallel resource management

Fangzhe Chang, Vijay Karamcheti, Zvi Kedem

Research output: Contribution to journalConference articlepeer-review


Parallel computing is becoming increasing central and mainstream, driven both by the widespread availability of commodity SMP and high-performance cluster platforms, as well as the growing use of parallelism in general-purpose applications such as image recognition, virtual reality, and media processing. In addition to performance requirements, the latter computations impose soft real-time constraints, necessitating efficient, predictable parallel resource management. In this paper, we propose a novel approach for increasing parallel system utilization while meeting application soft real-time deadlines. Our approach exploits the application tunability found in several general-purpose computations. Tunability refers to an application's ability to trade off resource requirements over time, while maintaining a desired level of output quality. We first describe language extensions to support tunability in the Calypso system, then characterize the performance benefits of tunability, using a synthetic task system to systematically identify its benefits. Our results show that application tunability is convenient to express and can significantly improve parallel system utilization for computations with predictability requirements.

Original languageEnglish (US)
Pages (from-to)749-758
Number of pages10
JournalProceedings of the International Parallel Processing Symposium, IPPS
StatePublished - 1999
EventProceedings of the 1999 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing - San Juan
Duration: Apr 12 1999Apr 16 1999

ASJC Scopus subject areas

  • Hardware and Architecture


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