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Multilevel Diffusion Schemes for Repartitioning of Adaptive Meshes
 JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
, 1997
"... For a large class of irregular mesh applications, the structure of the mesh changes from one phase of the computation to the next. Eventually, as the mesh evolves, the adapted mesh has to be repartitioned to ensure good load balance. If this new graph is partitioned from scratch, it may lead to an ..."
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Cited by 65 (7 self)
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For a large class of irregular mesh applications, the structure of the mesh changes from one phase of the computation to the next. Eventually, as the mesh evolves, the adapted mesh has to be repartitioned to ensure good load balance. If this new graph is partitioned from scratch, it may lead to an excessive migration of data among processors. In this paper, we present schemes for computing repartitionings of adaptively refined meshes that perform diffusion of
Graph partitioning for high performance scientific simulations. Computing Reviews 45(2
, 2004
"... ..."
Parallel Decomposition of Unstructured FEMMeshes
 Concurrency: Practice & Experience
, 1995
"... . We present a massively parallel algorithm for static and dynamic partitioning of unstructured FEMmeshes. The method consists of two parts. First a fast but inaccurate sequential clustering is determined which is used, together with a simple mapping heuristic, to map the mesh initially onto the pr ..."
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Cited by 41 (15 self)
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. We present a massively parallel algorithm for static and dynamic partitioning of unstructured FEMmeshes. The method consists of two parts. First a fast but inaccurate sequential clustering is determined which is used, together with a simple mapping heuristic, to map the mesh initially onto the processors of a massively parallel system. The second part of the method uses a massively parallel algorithm to remap and optimize the mesh decomposition taking several cost functions into account. It first calculates the amount of nodes that have to be migrated between pairs of clusters in order to obtain an optimal load balancing. In a second step, nodes to be migrated are chosen according to cost functions optimizing the amount and necessary communication and other measures which are important for the numerical solution method (like for example the aspect ratio of the resulting domains). The parallel parts of the method are implemented in C under Parix to run on the Parsytec GCel systems. R...
An Optimal Dynamic Load Balancing Algorithm
 Daresbury Laboratory
, 1995
"... The problem of redistributing work load on parallel computers is considered. An optimal redistribution algorithm, which minimises the Euclidean norm of the migrating load, is derived. The problem is further studied by modelling with the unsteady heat conduction equation. Relationship between this al ..."
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Cited by 40 (0 self)
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The problem of redistributing work load on parallel computers is considered. An optimal redistribution algorithm, which minimises the Euclidean norm of the migrating load, is derived. The problem is further studied by modelling with the unsteady heat conduction equation. Relationship between this algorithm and other dynamic load balancing algorithms is discussed. Convergence of the algorithm for special graphs is studied. Finally numerical results on randomly generated graphs are given to demonstrate the effectiveness of the algorithm. 1. Introduction To achieve good performance on a parallel computer, it is essential to maintain a balanced work load among all the processors of the computer. Sometimes the load can be balanced statically. However in many cases the load on each processor can not be predicted a priori. One example that demonstrates the need for both static and dynamic load balancing strategies, which is also the main motivation for this paper, is in the parallel finite e...
Diffusive Load Balancing Policies for Dynamic Applications
"... Massively parallel architectures require decentralized and scalable system policies. The paper presents and evaluates a set of local dynamic load balancing strategies inspired by diffusion and characterized by different scopes of locality: the goal is to compare their performance depending on the ..."
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Cited by 40 (4 self)
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Massively parallel architectures require decentralized and scalable system policies. The paper presents and evaluates a set of local dynamic load balancing strategies inspired by diffusion and characterized by different scopes of locality: the goal is to compare their performance depending on the application dynamicity. The paper shows that only slowly dynamic applications can take advantage of the diffusion policies with larger scope, because they are likely to base their decisions on non obsolete information only for limited load variations. Highly
Load Balancing Strategies For Distributed Memory Machines
 MultiScale Phenomena and Their Simulation
, 1997
"... Load balancing in large parallel systems with distributed memory is a difficult task often influencing the overall efficiency of applications substantially. A number of efficient distributed load balancing strategies have been developed in the recent years. Although they are currently not generally ..."
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Cited by 28 (1 self)
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Load balancing in large parallel systems with distributed memory is a difficult task often influencing the overall efficiency of applications substantially. A number of efficient distributed load balancing strategies have been developed in the recent years. Although they are currently not generally available as part of parallel operating systems, it is often not difficult to integrate them into applications. This paper gives a classification of different load balancing problems based on application characteristics. For the case of applications out of the field of scientific computing, useful methods are described in more detail.
On Runtime Parallel Scheduling for Processor Load Balancing
 IEEE Trans. Parallel and Distributed Systems
, 1997
"... Parallel scheduling is a new approach for load balancing. In parallel scheduling, all processors cooperate to schedule work. Parallel scheduling is able to accurately balance the load by using global load information at compiletime or runtime. It provides highquality load balancing. This paper pre ..."
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Cited by 22 (0 self)
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Parallel scheduling is a new approach for load balancing. In parallel scheduling, all processors cooperate to schedule work. Parallel scheduling is able to accurately balance the load by using global load information at compiletime or runtime. It provides highquality load balancing. This paper presents an overview of the parallel scheduling technique. Scheduling algorithms for tree, hypercube, and mesh networks are presented. These algorithms can fully balance the load and maximize locality 1. Introduction Static scheduling balances the workload before runtime and can be applied to problems with a predictable structure, which are called static problems. Dynamic scheduling performs scheduling activities concurrently at runtime, which applies to problems with an unpredictable structure, which are called dynamic problems. Static scheduling utilizes the knowledge of problem characteristics to reach a wellbalanced load [1, 2, 3, 4]. However, it is not able to balance the load for dynami...
Wavefront Diffusion and LMSR: Algorithms for Dynamic Repartitioning of Adaptive Meshes
 IEEE Transactions on Parallel and Distributed Systems
, 1998
"... Existing stateoftheart schemes for dynamic repartitioning of adaptive meshes can be classified as either diffusionbased schemes or scratchremap schemes. We present a new scratchremap scheme called LocallyMatched Multilevel ScratchRemap (or simply LMSR). The LMSR scheme tries to compute a par ..."
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Cited by 21 (7 self)
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Existing stateoftheart schemes for dynamic repartitioning of adaptive meshes can be classified as either diffusionbased schemes or scratchremap schemes. We present a new scratchremap scheme called LocallyMatched Multilevel ScratchRemap (or simply LMSR). The LMSR scheme tries to compute a partitioning that has a high overlap with the existing partitioning. We show that LMSR decreases the amount of vertex migration required to balance the graph compared to current scratchremap schemes, particularly for slightly imbalanced graphs. We describe a new diffusionbased scheme that we refer to as Wavefront Diffusion. In Wavefront Diffusion, the flow of vertices moves in a wavefront from overweight to underweight domains. We show that Wavefront Diffusion obtains significantly lower vertex migration requirements while maintaining similar or better edgecut results compared to existing diffusion algorithms, especially for highly imbalanced graphs. Furthermore, we compare Wavefront Diffusi...
Nearest Neighbor Algorithms for Load Balancing in Parallel Computers
, 1995
"... With nearest neighbor load balancing algorithms, a processor makes balancing decisions based on localized workload information and manages workload migrations within its neighborhood. This paper compares a couple of fairly wellknown nearest neighbor algorithms, the dimensionexchange (DE, for shor ..."
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Cited by 19 (2 self)
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With nearest neighbor load balancing algorithms, a processor makes balancing decisions based on localized workload information and manages workload migrations within its neighborhood. This paper compares a couple of fairly wellknown nearest neighbor algorithms, the dimensionexchange (DE, for short) and the diffusion (DF, for short) methods and their several variantsthe average dimensionexchange (ADE), the optimallytuned dimensionexchange (ODE), the local average diffusion (ADF) and the optimallytuned diffusion (ODF). The measures of interest are their efficiency in driving any initial workload distribution to a uniform distribution and their ability in controlling the growth of the variance among the processors' workloads. The comparison is made with respect to both oneport and allport communication architectures and in consideration of various implementation strategies including synchronous/asynchronous invocation policies and static/dynamic random workload behaviors. It t...
DataParallel Load Balancing Strategies
 Parallel Computing
, 1996
"... Programming irregular and dynamic dataparallel algorithms requires to take data distribution into account. The implementation of a load balancing algorithm is a quite difficult task for the programmer. However, a load balancing strategy may be developed independently of the application. The integra ..."
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Cited by 19 (0 self)
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Programming irregular and dynamic dataparallel algorithms requires to take data distribution into account. The implementation of a load balancing algorithm is a quite difficult task for the programmer. However, a load balancing strategy may be developed independently of the application. The integration of such a strategy in the dataparallel algorithm may be relevant to a library or a dataparallel compiler runtime. We propose load distribution dataparallel algorithms for a class of irregular dataparallel algorithms called stack algorithms. Our algorithms allow the use of regular and/or irregular communication patterns to exchange the works between processors. The results of theoretical analysis of these algorithms are presented. They allow a comparison of the different load balancing algorithms and the identification of criterion for the choice of a load balancing algorithm.