Performance modeling and analysis of correlated parallel computations

Lin, Wei-Ming

doi:10.1016/j.parco.2008.05.002

Cited by 5 publications

(2 citation statements)

References 34 publications

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“…These problems may be categorized as static [1,2,3,4,5,6,7,8,9] and dynamic [10,11,12,13,14] types of task allocation. Some of the other related methods have been reported in the literature, such as, Integer Programming [15], Load Balancing [16,17,18,19,20,21,22,23], Divide and Conquer [24], Grid Computing [25] and Branch and Bound [26,27].…”

Section: Introductionmentioning

confidence: 99%

A Smart Algorithm for Dynamic Task Allocation for Distributed Processing Environment

Govil¹

2011

IJCA

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A Distributed Processing Environment (DPE) consists of multiple autonomous computers that communicate through a communication media. In DPE a task is divided into many fractions and each of which is to be get processed. The task allocation problem can be explained in terms of number of tasks and number of processors available. In the present method propose a dynamic model for task allocation in DPE. Present method describes the allocation of m tasks in the environment of distributed processing with n processors (m>n) that completes in k number of phases. This method allocates the tasks to the processor to increases the performance of the DPE; and based on the inter task communication cost between executing task and another tasks. Residing cost and reallocation cost in various phases has also taken in consideration. On implemented the suggested algorithm we have obtained the phase wise optimal allocation and overall optimal cost. The run time complexity has been computed and compared with existing approaches. It is found that suggested algorithm is much better as compared to others.

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Section: Introductionmentioning

confidence: 99%

A Smart Algorithm for Dynamic Task Allocation for Distributed Processing Environment

Govil¹

2011

IJCA

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“…EasyFJP is targeted at parallelizing Java programs that follow a recursive (divide and conquer) structure, which is indeed applicable to a broad range of problems [58]. The contribution of this paper is a method for developing task-based Java parallel applications that (a) is based on application-level implicit FJP parallelism that does not require explicit usage of parallelism within the application code, (b) features integration with existing libraries and platforms for parallel and distributed development, and (c) offers a non-intrusive, rule-based mechanism to tune the same source code to various target execution environments.…”

Section: Introductionmentioning

confidence: 99%