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Post Silicon Power/Performance Optimization in the Presence of Process Variations Using Individual Well-Adaptive Body Biasing

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2 Author(s)
Justin Gregg ; Dept. of Electr. & Comput. Eng., Colorado State Univ., Fort Collins, CO ; Tom W. Chen

The economics of continued scaling of silicon process technologies beyond the 90-nm node will face significant challenges due to variability. The increasing relative magnitude of within die process variations will cause power-frequency distributions to widen, thus, reducing manufacturing yields. Mitigating the effects of these process variations can be done by using the proposed individual well-adaptive body biasing (IWABB) scheme of locally generated body biases. IWABB allows for highly localized circuit optimizations with very little overhead in silicon area and routing resources. We present two algorithms to find near-optimal configurations of these biases which can be applied as postsilicon tuning. The proposed IWABB scheme can improve an initial yield from 12% to 73%

Published in:

IEEE Transactions on Very Large Scale Integration (VLSI) Systems  (Volume:15 ,  Issue: 3 )