Power-aware Performance of Mixed Precision Linear Solvers for FPGAs and GPGPUs
Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Tennessee, USA
Symposium on Application Accelerators in High Performance Computing, 2010
@article{lee2010power,
title={Power-aware Performance of Mixed Precision Linear Solvers for FPGAs and GPGPUs},
author={Lee, J.K. and Sun, J. and Peterson, G.D. and Harrison, R.J. and Hinde, R.J.},
booktitle={Application Accelerators in High Performance Computing, 2010 Symposium, Papers},
year={2010}
}
Power has emerged as a significant constraint to high performance systems. We propose modeling power-based performance (performance/watt) and clock-based performance for GPGPUs and FPGAs. Based on the modeling, we perform a case-study with mixed precision linear solvers for a Xilinx XC5VLX330T FPGA and NVIDIA Tesla C1060 GPU. In the case-study, the FPGA shows power- and clock-based performance better than the GPGPU while the GPGPU shows better time-based performance.
February 18, 2011 by hgpu
