Name
Title | ||
|---|---|---|
Exploiting application tunability for efficient, predictable resource management in parallel and distributed systems |
Abstract | ||
|---|---|---|
Abstract 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 process - ing In addition to performance requirements, the latter computations impose soft real - time constraints, necessitating efficient, predictable parallel resource management Unfortunately, traditional resource management approaches in both parallel and real - time systems are inadequate for meeting this objec - tive; the parallel approaches focus primarily on improving application performance and/or system uti - lization at the cost of arbitrarily delaying a given application, while the real - time approaches are overly conservative sacrificing system utilization in order to meet application deadlines 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 require - ments over time, while maintaining a desired level of output quality In other words, a large allocation of resources in one stage of the computation's lifetime may compensate, in a parameterizable manner, for a smaller allocation in another stage We first describe language extensions to support tunability in the Calypso programming system, a component of the MILAN metacomputing project, and evaluate their expressiveness using an image processing application We then characterize the performance benefits of tunability, using a synthetic task system to systematically identify its benefits and shortcomings Our re - sults are very encouraging: application tunability is convenient to express, and can significantly improve parallel system utilization for computations with predictability requirements |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1006/jpdc.2000.1660 | J. Parallel Distrib. Comput. |
Keywords | DocType | Volume |
parallel and distributed computing,exploiting application tunability,resource management.,resource management,application tunability,predictable resource management,image processing,real time,resource utilization,virtual reality,real time systems,resource manager,image recognition,parallel computer,parallel systems | Journal | 60 |
Issue | ISSN | Citations |
11 | Journal of Parallel and Distributed Computing | 5 |
PageRank | References | Authors |
0.66 | 19 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fangzhe Chang | 1 | 248 | 15.32 |
| Vijay Karamcheti | 2 | 646 | 67.03 |
| Zvi Kedem | 3 | 710 | 369.44 |