Browsing by Subject "Inherent parallelism"
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Item Open Access Code scheduling for optimizing parallelism and data locality(Springer, 2010-08-09) Yemliha, T.; Kandemir, M.; Öztürk, Özcan; Kultursay, E.; Muralidhara, S. P.As chip multiprocessors proliferate, programming support for these devices is likely to receive a lot of attention in the near future. Parallelism and data locality are two critical issues in a chip multiprocessor environment. Unfortunately, most of the published work in the literature focuses only on one of these problems, and this can prevent one from achieving the best possible performance. The main goal of this paper is to propose and evaluate a compiler-directed code parallelization scheme, which considers both parallelism and data locality at the same time. Our compiler captures the inherent parallelism and data reuse in the application code being analyzed using a novel representation called the locality-parallelism graph (LPG). Our partitioning/scheduling algorithm assigns the nodes of this graph to the processors in the architecture and schedules them for execution. We implemented this algorithm and evaluated its effectiveness using a set of benchmark codes. The results collected so far indicate that our approach improves overall execution latency significantly. In this paper, we also introduce an ILP (Integer Linear Programming) based formulation of the problem, and implement the schedule obtained by the ILP solver. The results indicate that our approach gets within 4% of the ILP solution. © 2010 Springer-Verlag.Item Open Access An effective model to decompose linear programs for parallel solution(Springer, 1996-08) Pınar, Ali; Aykanat, CevdetAlthough inherent parallelism in the solution of block angulax Linear Programming (LP) problems has been exploited in many research works, the literature that addresses decomposing constraint matrices into block angular form for parallel solution is very rare and recent. We have previously proposed hypergraph models, which reduced the problem to the hypergraph partitioning problem. However, the quality of the results reported were limited due to the hypergraph partitioning tools we have used. Very recently, multilevel graph partitioning heuristics have been proposed leading to very successful graph partitioning tools; Chaco and Metis. In this paper, we propose an effective graph model to decompose matrices into block angular form, which reduces the problem to the well-known graph partitioning by vertex separator problem. We have experimented the validity of our proposed model with various LP problems selected from NETLIB and other sources. The results are very attractive both in terms of solution quality and running times. © Springer-Verlag Berlin Heidelberg 1996.