Heuristics for scheduling parameter sweep applications in grid environments
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TL;DR
This study proposes an adaptive scheduling algorithm for parameter sweep applications on the grid, modify standard heuristics for task/host assignment in perfectly predictable environments, and proposes an extension of Sufferage called XSufferage.
Abstract
The computational Grid provides a promising platform for the\nefficient execution of parameter sweep applications over very large parameter\nspaces. Scheduling such applications is challenging because target resources\nare heterogeneous, because their load and availability varies dynamically, and\nbecause tasks may share common data files. In this paper, we propose a\nscheduling algorithm for parameter sweep applications on the Grid. We consider\nstandard heuristics for task/host assignment (Max-min, Min-min, Sufferage), and\nwe propose an extension of Sufferage called XSufferage. Using simulation, we\ndemonstrate 3 results: 1) that XSufferage can take advantage of file sharing\nto achieve better performance than the other heuristics under a wide variety of\nload conditions, 2) that it is possible to characterize the environments under\nwhich different heuristics perform best, and 3) that it is possible to\ncharacterize the performance of different heuristics under the (realistic)\nassumption of varying accuracy of performance estimations.Pre-2018 CSE ID: CS1999-0632
