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Proceedings ArticleDOI

Fast and effective task scheduling in heterogeneous systems

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TLDR
In this article, modified versions of Fast Critical Path and Fast Load Balancing (FCP and FLB) are presented for compile-time list scheduling where the tasks' priorities are computed statically or dynamically.
Abstract
Recently (Proc. ACM Int. Conf. on Supercomput., 1999), we presented two very low-cost approaches to compile-time list scheduling where the tasks' priorities are computed statically or dynamically. For homogeneous systems, these two algorithms, called FCP (Fast Critical Path) and FLB (Fast Load Balancing), respectively, have been shown to yield a performance equivalent to other much more costly algorithms, such as MCP and ETF (Earliest Task First). In this paper, we present modified versions of FCP and FLB targeted at heterogeneous systems. We show that the modified versions yield a good overall performance, which is generally comparable to algorithms specifically designed for heterogeneous systems, such as HEFT (Heterogeneous Earliest Finish Time) or ERT (which are versions of MCP and ETF, respectively, using the task's completion time as the task priority). There are a few cases, mainly for irregular problems and large processor speed variance, where FCP's and FLB's performances drop to 32% and 63%, respectively. Considering the good overall performance and their very low cost, however, FCP and FLB are interesting options for scheduling very large problems on heterogeneous systems.

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Citations
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Journal ArticleDOI

List Scheduling Algorithm for Heterogeneous Systems by an Optimistic Cost Table

TL;DR: The analysis and experiments show that the PEFT algorithm outperforms the state-of-the-art list-based algorithms for heterogeneous systems in terms of schedule length ratio, efficiency, and frequency of best results.
Proceedings ArticleDOI

A hybrid heuristic for DAG scheduling on heterogeneous systems

TL;DR: A novel heuristic for DAG scheduling is presented, which is based upon solving a series of independent task scheduling problems and compares favourably with other related heuristics.
Book ChapterDOI

Comparative Evaluation Of The Robustness Of DAG Scheduling Heuristics

TL;DR: This paper analyzes the robustness of 20 static, makespan-centric, DAG scheduling heuristics of the literature and investigates how robustness and makespan are correlated.
Book ChapterDOI

An Experimental Investigation into the Rank Function of the Heterogeneous Earliest Finish Time Scheduling Algorithm

TL;DR: The findings indicate that the length of the schedule produced may be affected significantly by the scheme used, and suggest that the mean value based approach used by HEFT may not be a particularly good choice.
Journal ArticleDOI

A dynamic and reliability-driven scheduling algorithm for parallel real-time jobs executing on heterogeneous clusters

TL;DR: Results suggest that shortening scheduling times leads to a higher guarantee ratio, and if parallel scheduling algorithms are applied to shorten scheduling times, the performance of heterogeneous clusters will be further enhanced.
References
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Journal ArticleDOI

Hypertool: a programming aid for message-passing systems

TL;DR: Programming assistance, automation concepts, and their application to a message-passing system program development tool called Hypertool, which performs scheduling and handles the communication primitive insertion automatically, thereby increasing productivity and eliminating synchronization errors.
Journal ArticleDOI

Scheduling precedence graphs in systems with interprocessor communication times

TL;DR: The problem of nonpreemptively scheduling a set of m partially ordered tasks on n identical processors subject to interprocessor communication delays is studied in an effort to minimize the makespan and a new heuristic, called Earliest Task First (ETF), is designed and analyzed.
Journal ArticleDOI

Task Matching and Scheduling in Heterogeneous Computing Environments Using a Genetic-Algorithm-Based Approach

TL;DR: Simulation results for larger-sized problems showed that this genetic-algorithm-based approach outperformed two nonevolutionary heuristics and a random search.
Journal ArticleDOI

Grain size determination for parallel processing

TL;DR: Grain packing reduces total execution time by balancing execution time and communication time and used with an optimizing scheduler, it gives consistently better results than human-engineered scheduling and packing.
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