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Parallel Adaptive Tabu Search for Large Optimization Problems
, 1997
"... This paper presents a new approach for parallel tabu search based on adaptive parallelism. Adaptive parallelism demonstrates that massively parallel computing using a hundred of heterogeneous machines is feasible to solve large optimization problems. The parallel tabu search algorithm includes diffe ..."
Abstract

Cited by 6 (4 self)
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This paper presents a new approach for parallel tabu search based on adaptive parallelism. Adaptive parallelism demonstrates that massively parallel computing using a hundred of heterogeneous machines is feasible to solve large optimization problems. The parallel tabu search algorithm includes different tabu list sizes and new intensification/diversification mechanisms. Encouraging results have been obtained in solving the quadratic assignment problem. We have improved the best known solutions for some large realworld problems. 1 Motivation and goals Many interesting combinatorial optimization problems are NPhard, and then they cannot be solved exactly within a reasonable amount of time. Consequently, heuristics must be used to solve realworld problems. Tabu search (TS) is a general purpose heuristic (metaheuristic) that has been proposed by Glover [1]. TS has achieved widespread successes in solving practical optimization problems in different domains (resource management, proces...
A Parallel Adaptive Tabu Search Approach
 Parallel Computing
, 1998
"... This paper presents a new approach for parallel tabu search based on adaptive parallelism. Adaptive parallelism was used to dynamically adjust the parallelism degree of the application with respect to the system load. Adaptive parallelism demonstrates that highperformance computing using a hundred ..."
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Cited by 2 (0 self)
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This paper presents a new approach for parallel tabu search based on adaptive parallelism. Adaptive parallelism was used to dynamically adjust the parallelism degree of the application with respect to the system load. Adaptive parallelism demonstrates that highperformance computing using a hundred of heterogeneous workstations combined with massively parallel machines is feasible to solve large optimization problems. The parallel tabu search algorithm includes different tabu list sizes and new intensification/diversification mechanisms. Encouraging results have been obtained in solving the quadratic assignment problem. We have improved the best known solutions for some large realworld problems.
Design and Evaluation of a Datadistributed Massively Parallel Implementation of a Global Search Algorithm—DIRECT
, 2007
"... The present work aims at an efficient, portable, and robust design of a datadistributed massively parallel DIRECT, the deterministic global optimization algorithm widely used in multidisciplinary engineering design, biological science, and physical science applications. The original algorithm is mo ..."
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The present work aims at an efficient, portable, and robust design of a datadistributed massively parallel DIRECT, the deterministic global optimization algorithm widely used in multidisciplinary engineering design, biological science, and physical science applications. The original algorithm is modified to adapt to different problem scales and optimization (exploration vs. exploitation) goals. Enhanced with a memory reduction technique, dynamic data structures are used to organize local data, handle unpredictable memory requirements, reduce the memory usage, and share the data across multiple processors. The parallel scheme employs a multilevel functional and data parallelism to boost concurrency and mitigate the data dependency, thus improving the load balancing and scalability. In addition, checkpointing features are integrated to provide fault tolerance and hot restarts. Important algorithm modifications and design considerations are discussed regarding data structures, parallel schemes, error handling, and portability. Using several benchmark functions and realworld applications, the present work is evaluated in terms of optimization effectiveness, data structure efficiency, memory usage, parallel performance, and checkpointing overhead. Modeling and analysis techniques are
Adaptive Programming: Application to a Semi Supervised Point Prototype Clustering Algorithm
"... This paper presents an experiment on adaptive programming with a long lifespan application, a clustering algorithm used in the Magnetic Reasoning Imagery. Our goal is to provide tools that allow the application to benefit at the highest degree from the workstations availability in a Network of Works ..."
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This paper presents an experiment on adaptive programming with a long lifespan application, a clustering algorithm used in the Magnetic Reasoning Imagery. Our goal is to provide tools that allow the application to benefit at the highest degree from the workstations availability in a Network of Workstations with respect to the ownership aspect of such platforms. In addition, the fault risks are important in such environments preventing thus the parallel application from progress. The well suited solution of this problem is the use of a parallel adaptive system. Parallel adaptive systems constraint the application to adapt its parallelism degree to the load provided by the underlying environment. 1 Introduction Parallel and distributed programming has shown a great porgress both in methods and in implementation. This is due on one hand to the emergence of non costly workstations with constantly increasing performance and on the other hand to the requirements of a large class of compute ...
Une Taxonomie Des Algorithmes D'allocation Dynamique De Processus Dans Les Systèmes Parallèles Et Distribués
"... . In the design of distributed systems, the strategy used for process allocation has a great impact on the system performances. Most of the proposed dynamic allocation algorithms are based on heuristics, because of the impossibility to have a coherent global state of a distributed system and the tim ..."
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. In the design of distributed systems, the strategy used for process allocation has a great impact on the system performances. Most of the proposed dynamic allocation algorithms are based on heuristics, because of the impossibility to have a coherent global state of a distributed system and the time constraints of the process allocation decision making. In this report, a review and a comparative study of the different research studies in this field are presented. We propose a classification of the dynamic allocation algorithms, following the strategy used in the information exchange protocol to maintain the current state of a distributed system, and the process placement protocol to localize the destination of a process. The use of process migration mecanism is also analysed. Mots cl' es : Allocation dynamique de processus, Distribution de la charge, Localit'e, Migration de processus. Keywords : Dynamic process allocation, Load balancing, Locality, Process migration. 1 Introduction ...