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Journal ArticleDOI

Early prediction of MPP performance: the SP2, T3D, and Paragon experiences

Zhiwei Xu, +1 more
- Vol. 22, Iss: 7, pp 917-942
TLDR
The main contribution of this work lies in providing a systematic procedure to estimate the computational work-load, to determine the application attributes, and to reveal the communication overhead in using these MPPs.
Abstract
The performance of Massively Parallel Processors (MPPs) is attributed to a large number of machine and program factors. Software development for MPP applications is often very costly. The high cost is partially caused by a lack of early prediction of MPP performance. The program development cycle may iterate many times before achieving the desired performance level. In this paper, we present an early prediction scheme we have developed at the University of Southern California for reducing the cost of application software development. Using workload analysis and overhead estimation, our scheme optimizes the design of parallel algorithm before entering the tedious coding, debugging, and testing cycle of the applications. The scheme is generally applied at user/programmer level, not tied to any particular machine platform or any specific software environment. We have tested the effectiveness of this early performance prediction scheme by running the MIT/STAP benchmark programs on a 400-node IBM SP2 system at the Maui High-Performance Computing Center (MHPCC), on a 400-node Intel Paragon system at the San Diego Supercomputing Center (SDSC), and on a 128-node Cray T3D at the Cray Research Eagan Center in Wisconsin. Our prediction shows to be rather accurate compared with the actual performance measured on these machines. We use the SP2 data to illustrate the early prediction scheme. The main contribution of this work lies in providing a systematic procedure to estimate the computational work-load, to determine the application attributes, and to reveal the communication overhead in using these MPPs. These results can be applied to develop any MPP applications other than the STAP benchmarks by which this prediction scheme was developed.

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References
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Parallel and Distributed Computation: Numerical Methods

TL;DR: This work discusses parallel and distributed architectures, complexity measures, and communication and synchronization issues, and it presents both Jacobi and Gauss-Seidel iterations, which serve as algorithms of reference for many of the computational approaches addressed later.
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A bridging model for parallel computation

TL;DR: The bulk-synchronous parallel (BSP) model is introduced as a candidate for this role, and results quantifying its efficiency both in implementing high-level language features and algorithms, as well as in being implemented in hardware.
Book

Reevaluating Amdahl's law

TL;DR: Dans cet article, il est question de l'importance, pour la communaute scientifique informatique, de venir a bout du «blocage mental» contre le parallelisme massif impose par une mauvaise utilisation de la formule de Amdahl.
Journal ArticleDOI

Reevaluating Amdahl's law

TL;DR: In this article, Amdahl et al. describe a "blocage mental" contre le parallelisme massif impose par une mauvaise utilisation of the formule de Amdahls.
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Advanced Computer Architecture: Parallelism,Scalability,Programmability

Kai Hwang
TL;DR: This book deals with advanced computer architecture and parallel programming techniques and is suitable for use as a textbook in a one-semester graduate or senior course, offered by Computer Science, Computer Engineering, Electrical Engineering, or Industrial Engineering programs.
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