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Issue No.06 - November/December (2010 vol.27)
pp: 26-35
Minki Cho , Georgia Institute of Technology
Jason Schlessman , Princeton University
Hamid Mahmoodi , San Francisco State University
Marilyn Wolf , Georgia Institute of Technology
Saibal Mukhopadhyay , Georgia Institute of Technology
ABSTRACT
<p><it>Editor's note:</it></p><p>Due to the high density requirement for embedded memories, such memories are highly vulnerable to process variation&#x2013;induced failures. A conservative design approach can largely affect memory density and access performance. This article analyzes variation effects in SRAM and presents low-cost, adaptive postsilicon repair mechanisms.</p><p align="right"><it>&#x2014;Swarup Bhunia, Case Western Reserve University</it></p>
INDEX TERMS
design and test, low-power, multimedia, SRAM, reconfiguration, process variations, image processing, postsilicon adaptation
CITATION
Minki Cho, Jason Schlessman, Hamid Mahmoodi, Marilyn Wolf, Saibal Mukhopadhyay, "Postsilicon Adaptation for Low-Power SRAM under Process Variation", IEEE Design & Test of Computers, vol.27, no. 6, pp. 26-35, November/December 2010, doi:10.1109/MDT.2010.137
REFERENCES
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7. M. Cho et al., "Reconfigurable SRAM Architecture with Spatial Voltage Scaling for Low Power Mobile Multimedia Applications," to be published in IEEE Trans. Very Large Scale Integration (VLSI) Systems.
8. S. Mukhopadhyay et al., "Statistical Characterization and On-Chip Measurement Methods for Local Random Variability of a Process Using Sense-Amplifier-Based Test Structure," Proc. IEEE Int'l Solid State Circuits Conf. (ISSCC 07), IEEE Press, 2007, pp. 400-401, 611.
9. M. Yamaoka et al., "65 nm Low-Power High-Density SRAM Operable at 1.0 V under 3σ Systematic Variation Using Separate Vth Monitoring and Body Bias for NMOS and PMOS," IEEE Int'l Solid State Circuits Conf. (ISSCC 08), IEEE Press, 2008, pp. 383-385, 622.
10. N.N. Mojumder et al., "Self-Repairing SRAM Using On-Chip Detection and Compensation," IEEE Trans. Very Large Scale Integration (VLSI) Systems, vol. 18, no. 1, 2010, pp. 75-84.
11. Z. Wang et al., "Image Quality Assessment: From Error Visibility to Structural Similarity," IEEE Trans. Image Processing, vol. 13, no. 4, 2004, pp. 600-612.
12. J. Schlessman et al., "Hardware/Software Co-design of an FPGA-Based Embedded Tracking System," Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPRW 06), IEEE Press, 2006, pp. 123-133.
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