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Performance Analysis of General-Purpose Computation on Commodity Graphics Hardware: A Case Study Using Bioinformatics

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Abstract

Using modern graphics processing units for no-graphics high performance computing is motivated by their enhanced programmability, attractive cost/performance ratio and incredible growth in speed. Although the pipeline of a modern graphics processing unit (GPU) permits high throughput and more concurrency, they bring more complexities in analyzing the performance of GPU-based applications. In this paper, we identify factors that determine performance of GPU-based applications. We then classify them into three categories: data-linear, data-constant and computation-dependent. According to the characteristics of these factors, we propose a performance model for each factor. These models are then used to predict the performance of bio-sequence database scanning application on GPUs. Theoretical analyses and measurements show that our models can achieve precise performance predictions.

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Authors and Affiliations

  1. School of Computer Engineering, Nanyang Technological University, Singapore, 639798, Singapore

    Weiguo Liu & Wolfgang Müller-Wittig

  2. Division of Engineering, Science and Technology, UNSW Asia, Singapore, 248982, Singapore

    Bertil Schmidt

Authors
  1. Weiguo Liu
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  2. Bertil Schmidt
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  3. Wolfgang Müller-Wittig
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Correspondence to Weiguo Liu.

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Liu, W., Schmidt, B. & Müller-Wittig, W. Performance Analysis of General-Purpose Computation on Commodity Graphics Hardware: A Case Study Using Bioinformatics. J VLSI Sign Process Syst Sign Im 48, 209–221 (2007). https://doi.org/10.1007/s11265-007-0064-7

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  • DOI: https://doi.org/10.1007/s11265-007-0064-7

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