Application-Specific Power-Aware Workload Allocation for Voltage Scalable MPSoC Platforms

  • Authors:
  • Martino Ruggiero;Andrea Acquaviva;Davide Bertozzi;Luca Benini

  • Affiliations:
  • University of Bologna, DEIS, Viale Risorgimento, 2 - Bologna, Italy;University of Urbino, STI, Piazza Repubblica, 13 - Urbino, Italy;University of Ferrara, via Saragat, 1 - Ferrara, Italy;University of Bologna, DEIS, Viale Risorgimento, 2 - Bologna, Italy

  • Venue:
  • ICCD '05 Proceedings of the 2005 International Conference on Computer Design
  • Year:
  • 2005

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Abstract

In this paper, we address the problem of selecting the optimal number of processing cores and their operating voltage/frequency for a given workload, to minimize overall system power under application-dependent QoS constraints. Selecting the optimal system configuration is non-trivial, since it depends on task characteristics and system-level interaction effects among the cores. For this reason, our QoS-driven methodology for power aware partitioning and frequency selection is based on functional, cycle-accurate simulation on a virtual platform environment. The methodology, being application-specific, is demonstrated on the DES (Data Encryption System) algorithm, representative of a wider class of streaming applications with independent input data frames and regular workload.