Temperature aware microprocessor floorplanning considering application dependent power load

  • Authors:
  • Chun-Ta Chu;Xinyi Zhang;Lei He;Tom Tong Jing

  • Affiliations:
  • University of California at Los Angeles, CA;University of California at Los Angeles, CA;University of California at Los Angeles, CA;University of California at Los Angeles, CA

  • Venue:
  • Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper studies microprocessor floorplanning considering thermal and throughput optimization. We first develop a stochastic heat diffusion model taking into account the application dependent power load for thermal analysis. Then, we design the floorplanning algorithm based on this model. Experimental results show that, compared with the deterministic heat diffusion model, our model obtains up to 3.2°C reduction of the on-chip peak temperature, 1.25% reduction of the area, and 1.125x better CPI (cycles per instruction) performance, respectively. Compared with temperature aware floorplanning in the HOTSPOT tool set that ignores interconnect pipelining, our algorithm is up to 27x faster, reduces the peak temperature by up to 3°C, and also reduces CPI significantly with a negligible area overhead.