Abstract
A crucial step in DNA sequence analysis is mapping short sequences generated by next-generation instruments to a reference genome. In this paper, we focus on efficient online scheduling of multi-user parallel short sequence mapping queries on a multiprocessor system. With the availability of parallel execution models, the problem at hand becomes a moldable task scheduling problem where the number of processors needed to execute a task is determined by the scheduler. We propose an online scheduling algorithm to minimize the stretch of the tasks in the system. This metric provides improved fairness to small tasks compared to flow time metric and suits well to the nature of the problem. Experimental evaluation on two workload scenarios indicate that the algorithm results in significantly smaller stretch compared to a recent algorithm and it is more fair to small sized tasks.
This work was supported in parts by the U.S. DOE SciDAC Institute Grant DE-FC02-06ER2775; by the U.S. National Science Foundation under Grants CNS-0643969, OCI-0904809, OCI-0904802 and CNS-0403342; and an allocation of computing time from the Ohio Supercomputer Center.
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Saule, E., Bozdağ, D., Catalyurek, U.V. (2010). A Moldable Online Scheduling Algorithm and Its Application to Parallel Short Sequence Mapping. In: Frachtenberg, E., Schwiegelshohn, U. (eds) Job Scheduling Strategies for Parallel Processing. JSSPP 2010. Lecture Notes in Computer Science, vol 6253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16505-4_6
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DOI: https://doi.org/10.1007/978-3-642-16505-4_6
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