Load Balancing of Parallel Simulated Annealing on a Temporally Heterogeneous Cluster of Workstations

Moharil, S.; Lee, S.-Y.

doi:10.1109/ipdps.2007.370573

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…(2) If the cluster system provides different types of services [7], each type service request has a different load. When the system runs in a long time, it could not make full use of the CPU and I/O;…”

Section: Introductionmentioning

confidence: 99%

Dynamic Load Balancing Algorithm Based on Task Classification for Data Retrieval

Chen

Fang

Wang

et al. 2013

AMM

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Load balancing problems play a special role in the operation of parallel and distribution systems. The core technology of load balancing is the task scheduling. In order to achieve equally distribute the load on processors and maximize their utilities while minimizing the total task execution time, this article analyses a large number of data retrieval requests content. It shows different tasks have different resource occupation rate on the server node and the current server load is also different. The demand of different task types on CPU and I/O resources are not same. So, this paper presents a dynamic load balancing algorithm which is based on task classification, and applies it to the cluster system data retrieval.

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Section: Introductionmentioning

confidence: 99%

Dynamic Load Balancing Algorithm Based on Task Classification for Data Retrieval

Chen

Fang

Wang

et al. 2013

AMM

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“…Static load balancing is usually referred to as the mapping problem or scheduling problem [6]. In the literature, a large variety of methods such as randomized [7], round robin [1], simulated annealing [8], ant colony optimization and swarm optimization [9], and genetic algorithms [10] have been used to solve this problem. However, in a wide range of real time applications the workload is created during run-time [14] or the behavior of the workload change dramatically during run-time [15], and hence the advance knowledge of runtime behavior is unknown [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Load Balancing Framework for Real-time Applications in Message Passing Systems

Kabbany

Wanas²,

Hegazi

et al. 2010

Int J Parallel Prog

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Load balancing algorithms are designed essentially to equally distribute the load on processors and maximize their utilities while minimizing the total task execution time. In order to achieve these goals, the load-balancing mechanism should be "fair" in distributing the load across the different processors. This implies that the difference between the heaviest-loaded and the lightest-loaded processors should be minimized. Therefore, the load information on each processor must be updated such that the load-balancing mechanism can be more effective. In this work, we present an application independent dynamic algorithm for scheduling tasks and loadbalancing in message passing systems. We propose a DAG-based Dynamic Load Balancing algorithm for Real time applications (DAG-DLBR) that is designed to work dynamically to cope with possible changes in the load that might occur during runtime. This algorithm addresses the challenge of devising a load balancing scheme which judicially deals with the hybrid execution of existing real-time application (represented by a Direct Acyclic Graph (DAG)) together with newly arriving jobs. The main objective of this algorithm is to reduce response times of the newly arriving jobs while maintaining the time constrains of the existing DAG. To evaluate the performance of the DAG-DLBR algorithm, a comparison with the performance of two common dynamic load balancing algorithms is presented. This comparison is performed by evaluating, experimentally, the execution time of different load balancing algorithms on a homogenous real parallel machine. In addition, the values of load imbalance, the execution time, and the communication overhead time are evaluated analytically using different benchmarks as test-bed workloads. These workloads cover a wide range of dynamic applications with different task types. Experimental results illustrate the improved performance of the DAG-DLBR algorithm compared to both distributed and hierarchal based algorithms by at least 12 and 19%, respectively. This improvement is true for all workloads, even with highly dependent workload. The DAG-DLBR algorithm achieves lower computation time than its corresponding values of both the distributed and the hierarchical-based algorithms for 4, 8, 12 and 16 processors.

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Condition-based load balancing algorithm in distributed rendering

Mao

Shuang

2018

2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

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Load Balancing of Parallel Simulated Annealing on a Temporally Heterogeneous Cluster of Workstations

Abstract: Simulated annealing (SA) is a general-purpose optimiza-

Cited by 3 publications

References 9 publications

Dynamic Load Balancing Algorithm Based on Task Classification for Data Retrieval

Dynamic Load Balancing Algorithm Based on Task Classification for Data Retrieval

A Dynamic Load Balancing Framework for Real-time Applications in Message Passing Systems

Condition-based load balancing algorithm in distributed rendering

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