Performance analysis of reconfigurable processors using MVA analysis

  • Authors:

  • Ehsan Zadkhosh;Sepide Fatahi;Mahmood Ahmadi

  • Affiliations:

  • Department of Computer Engineering, Faculty of Engineering, University of Razi, Kermanshah, Iran;Department of Computer Engineering, Faculty of Engineering, University of Razi, Kermanshah, Iran;Department of Computer Engineering, Faculty of Engineering, University of Razi, Kermanshah, Iran

  • Venue:
  • ARC'12 Proceedings of the 8th international conference on Reconfigurable Computing: architectures, tools and applications
  • Year:
  • 2012

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Abstract

Collaboration of Reconfigurable processing elements in Grid Computing (CRGC) promises to provide both flexibility and performance to process computationally intensive tasks found in large applications. Reconfigurable computing provides much more flexibility than Application-Specific Integrated Circuits (ASICs) and much more performance than General-Purpose Processors (GPPs). GPPs, reconfigurable elements (RE) and hybrid (integration of GPPs and REs) elements are the main processing elements in the CRGC. In this paper, we propose closed queuing models for grid networks that incorporate the following processing elements: a GPP, a reconfigurable element (RE), and a hybrid element (combining a GPP with an RE). We examine two different models, one with feedback the other one without feedback. The performance metrics are the average response time and throughput. The proposed models are validated by take average response time and throughput of these models and simulation using OMNeTPP. Mean Value Analysis (MVA) is used to analytically compute the performance measures for these models. The comparison of the experimental (simulation) and analytical results suggest that the total average error for all the models with feedback and without feedback is less than 1.4% and 1.8%, respectively.