Power-Efficient Predication Techniques for Acceleration of Control Flow Execution on CGRA

  • Authors:
  • Kyuseung Han;Junwhan Ahn;Kiyoung Choi

  • Affiliations:
  • Seoul National University;Seoul National University;Seoul National University

  • Venue:
  • ACM Transactions on Architecture and Code Optimization (TACO)
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Coarse-grained reconfigurable architecture typically has an array of processing elements which are controlled by a centralized unit. This makes it difficult to execute programs having control divergence among PEs without predication. However, conventional predication techniques have a negative impact on both performance and power consumption due to longer instruction words and unnecessary instruction-fetching decoding nullifying steps. This article reveals performance and power issues in predicated execution which have not been well-addressed yet. Furthermore, it proposes fast and power-efficient predication mechanisms. Experiments conducted through gate-level simulation show that our mechanism improves energy-delay product by 11.9% to 23.8% on average.