Abstract. Many parallel applications are highly dynamic in nature. In some, computation and communication patterns change gradually dur-ing the run; in others those characteristics change abruptly. Such dy-namic applications require an adaptive load balancing strategy. We are exploring an adaptive approach based on multi-partition object-based decomposition, supported by object migration. For many applications, relatively infrequent load balancing is needed. In these cases it becomes economical to spend considerable computation time toward arriving at a nearly optimal mapping of objects to processors. We present an optimal-seeking branch and bound based strategy that finds nearly optimal so-lutions to such load balancing problems quickly, a...
. In this paper, we present a cohesive, practical load balancing framework that addresses many short...
International audienceThe most popular parallelization approach of the branch and bound algorithm co...
Load balancing in large parallel systems with distributed memory is a difficult task often influenci...
In parallel computing, obtaining maximal performance is often mandatory to solve large and complex p...
We present a contribution on dynamic load balancing for distributed and parallel object-oriented app...
In this paper, a parallel object collection (POC) model is introduced to support data parallelism in...
Parallel iterative applications often suffer from load imbalance, one of the most critical performan...
Migration is a fundamental mechanism for achieving load balancing and locality of references in para...
In this paper, a replication-based parallel object model will be presented first, where object repli...
Abstract. We present a contribution on dynamic load balancing for distributed and parallel object-or...
In this paper, a replication-based parallel object model will be presented first, where object repli...
In parallel iterative applications, computational efficiency is essential for addressing large probl...
This chapter describes a parallel optimization technique that incorporates a distributed load-balanc...
A parallel concurrent application runs most efficiently and quickly when the workload is distributed...
Load distribution is essential for efficient use of available processors in a parallel branch-and-bo...
. In this paper, we present a cohesive, practical load balancing framework that addresses many short...
International audienceThe most popular parallelization approach of the branch and bound algorithm co...
Load balancing in large parallel systems with distributed memory is a difficult task often influenci...
In parallel computing, obtaining maximal performance is often mandatory to solve large and complex p...
We present a contribution on dynamic load balancing for distributed and parallel object-oriented app...
In this paper, a parallel object collection (POC) model is introduced to support data parallelism in...
Parallel iterative applications often suffer from load imbalance, one of the most critical performan...
Migration is a fundamental mechanism for achieving load balancing and locality of references in para...
In this paper, a replication-based parallel object model will be presented first, where object repli...
Abstract. We present a contribution on dynamic load balancing for distributed and parallel object-or...
In this paper, a replication-based parallel object model will be presented first, where object repli...
In parallel iterative applications, computational efficiency is essential for addressing large probl...
This chapter describes a parallel optimization technique that incorporates a distributed load-balanc...
A parallel concurrent application runs most efficiently and quickly when the workload is distributed...
Load distribution is essential for efficient use of available processors in a parallel branch-and-bo...
. In this paper, we present a cohesive, practical load balancing framework that addresses many short...
International audienceThe most popular parallelization approach of the branch and bound algorithm co...
Load balancing in large parallel systems with distributed memory is a difficult task often influenci...