Co-scheduling algorithms for cache-partitioned systems

Guillaume Aupy 1, 2 Anne Benoit 3, 4 Loïc Pottier 4 Padma Raghavan 2 Yves Robert 3, 4, 5 Manu Shantharam 6
1 TADAAM - Topology-Aware System-Scale Data Management for High-Performance Computing
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest
2 Vanderbilt University [Nashville]
3 ROMA - Optimisation des ressources : modèles, algorithmes et ordonnancement
Inria Grenoble - Rhône-Alpes, LIP - Laboratoire de l'Informatique du Parallélisme
4 LIP - Laboratoire de l'Informatique du Parallélisme
5 The University of Tennessee [Knoxville]
6 San Diego Supercomputer Center [San Diego]
Abstract : Cache-partitioned architectures allow subsections of the shared last-level cache (LLC) to be exclusively reserved for some applications. This technique dramatically limits interactions between applications that are concurrently executing on a multi-core machine. Consider n applications that execute concurrently, with the objective to minimize the makespan, defined as the maximum completion time of the n applications. Key scheduling questions are: (i) which proportion of cache and (ii) how many processors should be given to each application? Here, we assign rational numbers of processors to each application, since they can be shared across applications through multi-threading. In this paper, we provide answers to (i) and (ii) for perfectly parallel applications. Even though the problem is shown to be NP-complete, we give key elements to determine the subset of applications that should share the LLC (while remaining ones only use their smaller private cache). Building upon these results, we design efficient heuristics for general applications. Extensive simulations demonstrate the usefulness of co-scheduling when our efficient cache partitioning strategies are deployed.
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Communication dans un congrès
APDCM 2017 - 19th Workshop on Advances in Parallel and Distributed Computational Models, May 2017, Orlando (FL), United States. IEEE, pp.1-10, Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2017 IEEE International. 〈10.1109/IPDPSW.2017.60〉
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Guillaume Aupy, Anne Benoit, Loïc Pottier, Padma Raghavan, Yves Robert, et al.. Co-scheduling algorithms for cache-partitioned systems. APDCM 2017 - 19th Workshop on Advances in Parallel and Distributed Computational Models, May 2017, Orlando (FL), United States. IEEE, pp.1-10, Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2017 IEEE International. 〈10.1109/IPDPSW.2017.60〉. 〈hal-01654660〉

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