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21
Data Redistribution Algorithms For Heterogeneous Processor Rings
, 2004
"... We consider the problem of redistributing data on homogeneous and heterogeneous ring of processors. The problem arises in several applications, each time after that a loadbalancing mechanism is invoked (but we do not discuss the loadbalancing mechanism itself). We provide algorithms that aim at op ..."
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Cited by 7 (5 self)
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We consider the problem of redistributing data on homogeneous and heterogeneous ring of processors. The problem arises in several applications, each time after that a loadbalancing mechanism is invoked (but we do not discuss the loadbalancing mechanism itself). We provide algorithms that aim at optimizing the data redistribution, both for unidirectional and bidirectional rings, and we give complete proofs of correctness. One major contribution of the paper is that we are able to prove the optimality of the proposed algorithms in all cases except that of a bidirectional heterogeneous ring, for which the problem remains open.
Mapping and LoadBalancing Iterative Computations
 IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
, 2004
"... This paper is devoted to mapping iterative algorithms onto heterogeneous clusters. The application data is partitioned over the processors, which are arranged along a virtual ring. At each iteration, independent calculations are carried out in parallel, and some communications take place between c ..."
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Cited by 4 (0 self)
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This paper is devoted to mapping iterative algorithms onto heterogeneous clusters. The application data is partitioned over the processors, which are arranged along a virtual ring. At each iteration, independent calculations are carried out in parallel, and some communications take place between consecutive processors in the ring. The question is to determine how to slice the application data into chunks, and to assign these chunks to the processors, so that the total execution time is minimized. One major difficulty is to embed a processor ring into a network that typically is not fully connected, so that some communication links have to be shared by several processor pairs. We establish a complexity result that assesses the difficulty of this problem, and we design a practical heuristic that provides efficient mapping, routing, linksharing, and data distribution schemes.
Scheduling and Data Redistribution Strategies on Star Platforms
"... In this work we are interested in the problem of scheduling and redistributing data on masterslave platforms. We consider the case were the workers possess initial loads, some of which having to be redistributed in order to balance their completion times. We assume that the data consists of indepen ..."
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Cited by 4 (3 self)
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In this work we are interested in the problem of scheduling and redistributing data on masterslave platforms. We consider the case were the workers possess initial loads, some of which having to be redistributed in order to balance their completion times. We assume that the data consists of independent and identical tasks. As the general case is NPcomplete in the strong sense, we propose three heuristics. Simulations consolidate the theoretical results. 1.
K.A.Hawick, Resource Descriptions for Job Scheduling in DISCWorld
 Proc 5th IDEA Workshop, Fremantle
, 1998
"... ..."
Load Balancing for Minimizing Execution Time of a Target Job on a Network of Heterogeneous Workstations
 Proc. 6 th Workshop on Job Scheduling Strategies for Parallel Processing, Lecture Notes in Computer Science
, 2000
"... Abstract. A network of workstations (NOWs) may be employed for high performance computing where execution time of a target job is to be minimized. Job arrival rate and size are “random ” on a NOWs. In such an environment, partitioning (load balancing) a target job based on only the first order momen ..."
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Cited by 2 (0 self)
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Abstract. A network of workstations (NOWs) may be employed for high performance computing where execution time of a target job is to be minimized. Job arrival rate and size are “random ” on a NOWs. In such an environment, partitioning (load balancing) a target job based on only the first order moments (means) of system parameters is not optimal. In this paper, it is proposed to consider the second order moments (standard deviations) also in load balancing in order to minimize execution time of a target job on a set of workstations where the roundrobin job scheduling policy is adopted. It has been verified through computer simulation that the proposed static and dynamic load balancing schemes can significantly reduce execution time of a target job in a NOWs environment, compared to cases where only the means of the parameters are used.
TreeBased Parallel LoadBalancing Methods for SolutionAdaptive Finite Element Graphs on Distributed memory Multicomputers
 IEEE Transactions on parallel and Distributed Systems
, 1999
"... Abstract—To solve the load imbalance problem of a solutionadaptive finite element application program on a distributed memory multicomputer, nodes of a refined finite element graph can be remapped to processors or load of a refined finite element graph can be redistributed based on the current load ..."
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Cited by 2 (1 self)
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Abstract—To solve the load imbalance problem of a solutionadaptive finite element application program on a distributed memory multicomputer, nodes of a refined finite element graph can be remapped to processors or load of a refined finite element graph can be redistributed based on the current load of each processor. For the former case, remapping can be performed by some fast mapping algorithms. For the latter case, a loadbalancing algorithm can be applied to balance the computational load of each processor. In this paper, three treebased parallel loadbalancing methods, the MCSTLB method, the BTLB method, and the CBTLB method, were proposed to deal with the load imbalance problems of solutionadaptive finite element application programs. To evaluate the performance of the proposed methods, we have implemented those methods along with three mapping methods, the AE/ORB method, the AE/MC method, and the MLkP method, on an SP2 parallel machine. Three criteria, the execution time of mapping/loadbalancing methods, the execution time of a solutionadaptive finite element application program under different mapping/loadbalancing methods, and the speedups achieved by mapping/loadbalancing methods for a solutionadaptive finite element application program, are used for the performance evaluation. The experimental results show that 1) if the initial mapping is performed by a mapping method and the same mapping method and loadbalancing methods were used in each refinement to balance the load of processors, the execution time of an application program under a loadbalancing method is always shorter than that of the mapping method, and 2) the execution time of an application program under the CBTLB method is shorter than that of the BTLB method and the MCSTLB method. Index Terms—Distributed memory multicomputers, partitioning, mapping, load balancing, solutionadaptive finite element graphs. ————————— — F ——————————
Static LoadBalancing Techniques For Iterative Computations On Heterogeneous Clusters
, 2003
"... This paper is devoted to static load balancing techniques for mapping iterative algorithms onto heterogeneous clusters. The application data is partitioned over the processors. At each iteration, independent calculations are carried out in parallel, and some communications take place. The questio ..."
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Cited by 1 (1 self)
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This paper is devoted to static load balancing techniques for mapping iterative algorithms onto heterogeneous clusters. The application data is partitioned over the processors. At each iteration, independent calculations are carried out in parallel, and some communications take place. The question
Scheduling and data redistribution strategies on star platforms
, 2006
"... Scheduling and data redistribution strategies on star platforms ..."
Hélène Renard,
, 2003
"... Static loadbalancing techniques for iterative computations on heterogeneous clusters ..."
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Static loadbalancing techniques for iterative computations on heterogeneous clusters