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Task Assignment Algorithms for Heterogeneous Multiprocessors

Published:06 October 2014Publication History
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Abstract

Consider the problem of assigning implicit-deadline sporadic tasks on a heterogeneous multiprocessor platform comprising a constant number (denoted by t) of distinct types of processors—such a platform is referred to as a t-type platform. We present two algorithms, LPGIM and LPGNM, each providing the following guarantee. For a given t-type platform and a task set, if there exists a task assignment such that tasks can be scheduled to meet their deadlines by allowing them to migrate only between processors of the same type (intra-migrative), then: (i) LPGIM succeeds in finding such an assignment where the same restriction on task migration applies (intra-migrative) but given a platform in which only one processor of each type is 1 + α × t-1/t times faster and (ii) LPGNM succeeds in finding a task assignment where tasks are not allowed to migrate between processors (non-migrative) but given a platform in which every processor is 1 + α times faster. The parameter α is a property of the task set; it is the maximum of all the task utilizations that are no greater than one. To the best of our knowledge, for t-type heterogeneous multiprocessors: (i) for the problem of intra-migrative task assignment, no previous algorithm exists with a proven bound and hence our algorithm, LPGIM, is the first of its kind and (ii) for the problem of non-migrative task assignment, our algorithm, LPGNM, has superior performance compared to state-of-the-art.

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          • Published in

            cover image ACM Transactions on Embedded Computing Systems
            ACM Transactions on Embedded Computing Systems  Volume 13, Issue 5s
            Special Issue on Risk and Trust in Embedded Critical Systems, Special Issue on Real-Time, Embedded and Cyber-Physical Systems, Special Issue on Virtual Prototyping of Parallel and Embedded Systems (ViPES)
            November 2014
            501 pages
            ISSN:1539-9087
            EISSN:1558-3465
            DOI:10.1145/2660459
            Issue’s Table of Contents

            Copyright © 2014 ACM

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 6 October 2014
            • Accepted: 1 May 2014
            • Received: 1 September 2013
            Published in tecs Volume 13, Issue 5s

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