article · 1996
Maximizing Speedup Through Self-Tuning of Processor Allocation
Nguyen Thi Anh Thu, Raj Vaswani, John Zahorjan
Cited by 3Abstract and details only
Abstract
We address the problem of maximizing application speedup through runtime, self-selection of an appropriate number of processors on which to run. Automatic, runtime selection of processor allocations is important because many parallel applications exhibit peak speedups at allocations that are data or time dependent. We propose the use of a runtime system that: (a) dynamically measures job efficiencies at different allocations, (b) uses these measurements to calculate speedups, and (c) automatically adjusts a job's processor allocation to maximize its speedup. Using a set of 10 applications that includes both hand-coded parallel programs and compiler-parallelized sequential programs, we show that our runtime system can reliably determine dynamic allocations that match the best possible static allocation, and that it has the potential to find dynamic allocations that outperform any static allocation. 1. Introduction We consider the problem of maximizing the speedup of an individual paral...
Cite this paper
Thu, N. T. A., Vaswani, R., & Zahorjan, J. (1996). Maximizing Speedup Through Self-Tuning of Processor Allocation.
Thu, Nguyen Thi Anh, et al. “Maximizing Speedup Through Self-Tuning of Processor Allocation.” 1996.
Thu, Nguyen Thi Anh, Raj Vaswani, and John Zahorjan. 1996. “Maximizing Speedup Through Self-Tuning of Processor Allocation.”
Thu, N.T.A., Vaswani, R. and Zahorjan, J. (1996) ‘Maximizing Speedup Through Self-Tuning of Processor Allocation’.
@article{thu1996maximizing,
title = {{Maximizing Speedup Through Self-Tuning of Processor Allocation}},
author = {Thu, Nguyen Thi Anh and Vaswani, Raj and Zahorjan, John},
year = {1996}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.