@conference {gupta2009tribeca, title = {Tribeca: design for PVT variations with local recovery and fine-grained adaptation}, booktitle = {2009 42nd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)}, year = {2009}, pages = {435{\textendash}446}, publisher = {IEEE}, organization = {IEEE}, address = {New York, NY, USA}, abstract = {

With continued advances in CMOS technology, parameter variations are emerging as a major design challenge. Irregularities during the fabrication of a microprocessor and variations of voltage and temperature during its operation widen worst-case timing margins of the design - degrading performance significantly. Because runtime variations like supply voltage droops and temperature fluctuations depend on the activity signature of the processor{\textquoteright}s workload, there are several opportunities to improve performance by dynamically adapting margins. This paper explores the power-performance efficiency gains that result from designing for typical conditions while dynamically tuning frequency and voltage to accommodate the runtime behavior of workloads. Such a design depends on a fail-safe mechanism that allows it to protect against margin violations during adaptation; we evaluate several such mechanisms, and we propose a local recovery scheme that exploits spatial variation among the units of the processor. While a processor designed for worst-case conditions might only be capable of a frequency that is 75\% of an ideal processor with no parameter variations, we show that a fine-grained global frequency tuning mechanism improves power-performance efficiency (BIPS\ 3\ /W) by 40\% while operating at 91\% of an ideal processor{\textquoteright}s frequency. Moreover, a per-unit voltage tuning mechanism aims to reduce the effect of within-die spatial variations to provide a 55\% increase in power-performance efficiency. The benefits reported are clearly substantial in light of the \<1\% area overhead relative to existing global recovery mechanisms.

}, url = {https://doi.org/10.1145/1669112.1669168}, author = {Meeta Gupta and Jude Rivers and Pradip Bose and Gu Wei and David Brooks} }