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Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing (2002)
| Venue: | IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS |
| Citations: | 254 - 0 self |
BibTeX
@ARTICLE{Topcuoglu02performance-effectiveand,
author = {Haluk Topcuoglu and Min-you Wu and et al.},
title = {Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing},
journal = {IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS},
year = {2002},
volume = {13},
number = {3},
pages = {260--274}
}
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Abstract
Efficient application scheduling is critical for achieving high performance in heterogeneous computing environments. The application scheduling problem has been shown to be NP-complete in general cases as well as in several restricted cases. Because of its key importance, this problem has been extensively studied and various algorithms have been proposed in the literature which are mainly for systems with homogeneous processors. Although there are a few algorithms in the literature for heterogeneous processors, they usually require significantly high scheduling costs and they may not deliver good quality schedules with lower costs. In this paper, we present two novel scheduling algorithms for a bounded number of heterogeneous processors with an objective to simultaneously meet high performance and fast scheduling time, which are called the Heterogeneous Earliest-Finish-Time (HEFT) algorithm and the Critical-Path-on-a-Processor (CPOP) algorithm. The HEFT algorithm selects the task with the highest upward rank value at each step and assigns the selected task to the processor, which minimizes its earliest finish time with an insertion-based approach. On the other hand, the CPOP algorithm uses the summation of upward and downward rank values for prioritizing tasks. Another difference is in the processor selection phase, which schedules the critical tasks onto the processor that minimizes the total execution time of the critical tasks. In order to provide a robust and unbiased comparison with the related work, a parametric graph generator was designed to generate weighted directed acyclic graphs with various characteristics. The comparison study, based on both randomly generated graphs and the graphs of some real applications, shows that our scheduling algorithms significantly surpass previous approaches in terms of both quality and cost of schedules, which are mainly presented with schedule length ratio, speedup, frequency of best results, and average scheduling time metrics.
Keyphrases
low-complexity task scheduling critical task high performance heterogeneous processor high scheduling cost various algorithm several restricted case heft algorithm application scheduling problem real application general case related work processor selection phase bounded number parametric graph generator total execution time heterogeneous earliest-finish-time insertion-based approach homogeneous processor unbiased comparison comparison study upward rank value average scheduling time metric scheduling time acyclic graph good quality schedule various characteristic downward rank value schedule length ratio finish time key importance previous approach cpop algorithm efficient application scheduling
