ACM Home Page
Please provide us with feedback. Feedback
Power and performance tradeoffs with process variation resilient adaptive cache architectures
Full text PdfPdf (292 KB)
Source
SBCCI archive
Proceedings of the 21st annual symposium on Integrated circuits and system design table of contents
Gramado, Brazil
SESSION: Advances in low power design and power management table of contents
Pages 123-128  
Year of Publication: 2008
ISBN:978-1-60558-231-3
Authors
Mahmoud Bennaser  Kuwait University, Safat, Kuwait
Csaba Andras Moritz  University of Massachusetts, Amherst, MA, USA
Sponsors
ACM: Association for Computing Machinery
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 2,   Downloads (12 Months): 26,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1404371.1404410
What is a DOI?

ABSTRACT

As the transistor feature size becomes smaller, circuits show an increased sensitivity to the fluctuations of process parameters. These variations could severely affect the performance and power consumption of processors. In this paper, we establish what the overall leakage power is due to process variations in a cache and show how power and performance can be managed with the help of an adaptive cache sub-system despite process variation effects. The distribution of the cache leakage power was determined by performing Monte-Carlo simulations at different supply voltages, threshold voltages, and transistor lengths on a complete cache design before and after incorporating leakage optimizations. Simulation results show that our adaptive data cache is process variations resilient and can achieve in average 10% performance improvement on SPEC2000 applications in a superscalar processor, in conjunction with 6X reduction in the mean leakage power compared with a conventional design.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Predictive technology model. Nanoscale Integration and Modeling Group, ASU. http:// www.eas.asu.edu/~ptm
 
2
The Standard Performance Evaluation Corporation, 2000. http://www.spec.org
 
3
D. Boning and S. Nassif. "Models of process variations in device and interconnect". In Design of High-Performance Microprocessor Circuits, A. Chandrakasan, chapter 6, pp. 98--115, IEEE Press 2001.
 
4
K. Bowman, X. Tang, J. Eble, and J. Menldl. "Impact of extrinsic and intrinsic parameter fluctuations on CMOS circuit performance". In IEEE Journal of Solid- State Circuits, volume 35, pp. 1186--1193, August 2000.
5
 
6
 
7
R. Chau, S. Datta, M. Doczy, J. Kavalieros, and M. Metz. "Gate dielectric scaling for high-performance CMOS: from SiO2 to High-K". In the International Workshop on Gate Insulator, pp. 124--126, November 2003.
 
8
D. Burnett, K. Erington, C. Subramanian, and K. Baker. "Implications of fundamental threshold voltage variations for high-density SRAM and logic circuits". Symposium on VLSI Technology, pp. 14--15, June 1994.
 
9
 
10
D. C. Burger and T. M. Austin. "The SimpleScalar tool set, version 2.0". Technical Report CS-TR-1997-1342, University of Wisconsin, Madison, June 1997.

Collaborative Colleagues:
Mahmoud Bennaser: colleagues
Csaba Andras Moritz: colleagues