Is Statistical Timing Statistically Significant? DAC 2004, Panel Discussion, Session 41 Chandu Visweswariah IBM Thomas J. Watson Research Center Yorktown.

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Presentation transcript:

Is Statistical Timing Statistically Significant? DAC 2004, Panel Discussion, Session 41 Chandu Visweswariah IBM Thomas J. Watson Research Center Yorktown Heights, NY

Performance Technology generation Is this worth a huge investment? The march of technology

Corner-based vs. statistical n = # independent sources of variation (say 9)  = total variability in critical path delay (say 5%) Fractional increase in frequency with a 3  sign-off instead of 3  n sign-off Assumes sources of variation are roughly equally significant

Corner-based vs. statistical

Too leaky Simultaneous power/timing sign-off Too slow Probability Vt Good chips

Where will the models come from? Clearly, the IDMs have an advantage Table-based delay modeling formats are not as conducive to statistical timing as equation-based formats

Can statistical timers handle the size? 2.1M gate design timed in 69 minutes with 10.9 GB memory 1.1M gate design timed in 110 minutes (dominated by load time) with 4.3 GB memory

BEOL early-mode variability on ASIC part Pessimism reduction -3  slack: -162 ps Exhaustive corner analysis: -225 ps

How will it be phased in? Phase 1 –true 3  timing sign-off with statistical timing Phase 2 –use statistical timing to guide the physical synthesis and routing optimization (implicit robustness credit) Phase 3 –further reduce performance  by actively targeting robustness (explicit robustness credit) Phase 4 –with the mainstream availability of at-speed test, enable yield/performance tradeoffs

Propositions/predictions 1.Variability is proportionately increasing; therefore, a new paradigm is required 2.Correlated vs. independent variability matters 3.Statistical timing tools are rising to the challenge 4.Robustness is an important metric 5.Statistical treatment of variability will pervade all aspects of chip design and manufacturing 6.ASICs and processors will both benefit (in that order)

Statistical prediction (ASICs) With a probability of ____%, statistical design analysis will have been used at the _______ technology node by the year ______, to solve the problem of ___________________________. The technical foundation of this statistical design analysis will be __________________________ ______________________. 90 nm 2006 performance pessimism 99 (in part) techniques like those of paper 21.1