Essential Issues in Multiprocessor Systems

Gajski,; Peir, Jib-Kwon

doi:10.1109/mc.1985.1662920

Cited by 88 publications

(20 citation statements)

References 35 publications

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“…(d)Evaluation of the stresses within each element of the structure by substituting the known nodal displacements into (4).…”

Section: The Fe Displacement Methodsmentioning

confidence: 99%

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Parallel processing techniques for FE analysis: System solution

Zois

1988

Computers & Structures

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“…(d)Evaluation of the stresses within each element of the structure by substituting the known nodal displacements into (4).…”

Section: The Fe Displacement Methodsmentioning

confidence: 99%

“…In the late 1960s and early 1970s, the general purpose serial computers such as CDC 6600 or IBM 360/91 [4] began to use multiple dedicated functional units, e.g. floating point adders, multipliers, working in parallel to improve the speed of the program execution.…”

Section: Introductionmentioning

confidence: 99%

Parallel processing techniques for FE analysis: System solution

Zois

1988

Computers & Structures

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“…They make their assignments using algorithms rooted in polices like first-in-first-out, round-robin, shortest-job-first and others [8], [18]. The policy which a scheduler uses depends upon which computing goals wish to be supported.…”

Section: Schedulersmentioning

confidence: 99%

Visualizing performance debugging

et al. 1989

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This article discusses visualizing performance of parallel and sequential computations using the Programming and Instrumentation Environment (PIE) as an example. First, the importance of being able to visualize the performance of a computation is demonstrated. Secondly, an easy guide to one way, the PIE way, of his visualization process is presented. This is followed by examples of concrete uses of the environment. Finally, some of the pressing issues concerning measuring performance are discussed.Three issues are stressed in this article:1. Visualization of program performance is necessary for fast, correct performance debugging.2. PIE is a powerful and useful implementation for supporting visualization. It is also a dramatic teaching assistant in that it visually shows actions like forking, scheduling, etc.3. PIE provides complete support for visualization. The system is aware of issues like program replay, suitably presenting performance data, compensation for perturbation by the measurement facility and support for multiple architectures and languages .

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“…Scheduling is a function that assign job to the different processors [6]. It's a two step process, namely processor allocation and assignment.…”

Section: Introductionmentioning

confidence: 99%

Classification of Task Partitioning and Load Balancing Strategies in Distributed Parallel Computing Systems

Khan¹,

Ali²

2012

IJCA

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Distribution of the tasks amongst the various computing nodes is itself an intellectually challenging problem in the high performance distributed computing systems. To choose the appropriate strategy for the required system is difficult without the meaningful comparison of the existing task partitioning and load balancing strategies. The effectiveness of the strategy depend on the number of factors-efficiency, interconnection topology, communication mode, program structure, throughput and computing capabilities of the structure. A number of task partitioning and load balancing strategies have been proposed, each of which perform remarkable results under different circumstances. The main goal of the paper is to unravel the mystery of strategies and to classify when and where each strategy is appropriate. In this paper, taxonomy of task partitioning and load balancing is presented in an attempt to provide a common terminology and classification mechanism.

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Essential Issues in Multiprocessor Systems

Cited by 88 publications

References 35 publications

Parallel processing techniques for FE analysis: System solution

Parallel processing techniques for FE analysis: System solution

Visualizing performance debugging

Classification of Task Partitioning and Load Balancing Strategies in Distributed Parallel Computing Systems

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