Accelerating DSP Applications on a Mixed Granularity Platform with a New Reconfigurable Coarse-Grain Data-Path

Authors:
M. D. Galanis;G. Theodoridis;S. Tragoudas;D. Soudris;C. E. Goutis
Affiliations:
University of Patras, Greece;Aristotle University, Greece;Southern Illinois University, USA;Democritus University, Greece;University of Patras, Greece
Venue:
FCCM '04 Proceedings of the 12th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Year:
2004

Citing 0
Cited 1

Energy Efficient Coarse-Grain Reconfigurable Array for Accelerating Digital Signal Processing

Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a high performance reconfigurable coarse-grain data-path, part of a mixed-granularity reconfigurable platform, is presented. The computational resources are coarse grain components of the same type. An automated methodology for mapping DSP applications on the data-path is also presented, and it is based on unsophisticated, yet efficient, algorithms. Results on DSP benchmarks show the performance improvements over previously published high-performance data-paths.