TY - GEN
T1 - Optimized self-tuning for circuit aging
AU - Mintarno, Evelyn
AU - Skaf, Joëlle
AU - Zheng, Rui
AU - Velamala, Jyothi
AU - Cao, Yu
AU - Boyd, Stephen
AU - Dutton, Robert W.
AU - Mitra, Subhasish
PY - 2010
Y1 - 2010
N2 - We present a framework and control policies for optimizing dynamic control of various self-tuning parameters over lifetime in the presence of circuit aging. Our framework introduces dynamic cooling as one of the self-tuning parameters, in addition to supply voltage and clock frequency. Our optimized self-tuning satisfies performance constraints at all times and maximizes a lifetime computational power efficiency (LCPE) metric, which is defined as the total number of clock cycles achieved over lifetime divided by the total energy consumed over lifetime. Our framework features three control policies: 1. Progressive-worst-case-aging (PWCA), which assumes worst-case aging at all times; 2. Progressive-on-state-aging (POSA), which estimates aging by tracking active/sleep mode, and then assumes worst-case aging in active mode and long recovery effects in sleep mode; 3. Progressive-real-time-aging-assisted (PRTA), which estimates the actual amount of aging and initiates optimized control action. Simulation results on benchmark circuits, using aging models validated by 45nm CMOS stress measurements, demonstrate the practicality and effectiveness of our approach. We also analyze design constraints and derive system design guidelines to maximize self-tuning benefits.
AB - We present a framework and control policies for optimizing dynamic control of various self-tuning parameters over lifetime in the presence of circuit aging. Our framework introduces dynamic cooling as one of the self-tuning parameters, in addition to supply voltage and clock frequency. Our optimized self-tuning satisfies performance constraints at all times and maximizes a lifetime computational power efficiency (LCPE) metric, which is defined as the total number of clock cycles achieved over lifetime divided by the total energy consumed over lifetime. Our framework features three control policies: 1. Progressive-worst-case-aging (PWCA), which assumes worst-case aging at all times; 2. Progressive-on-state-aging (POSA), which estimates aging by tracking active/sleep mode, and then assumes worst-case aging in active mode and long recovery effects in sleep mode; 3. Progressive-real-time-aging-assisted (PRTA), which estimates the actual amount of aging and initiates optimized control action. Simulation results on benchmark circuits, using aging models validated by 45nm CMOS stress measurements, demonstrate the practicality and effectiveness of our approach. We also analyze design constraints and derive system design guidelines to maximize self-tuning benefits.
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U2 - 10.1109/date.2010.5457140
DO - 10.1109/date.2010.5457140
M3 - Conference contribution
AN - SCOPUS:77953113043
SN - 9783981080162
T3 - Proceedings -Design, Automation and Test in Europe, DATE
SP - 586
EP - 591
BT - DATE 10 - Design, Automation and Test in Europe
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Design, Automation and Test in Europe Conference and Exhibition, DATE 2010
Y2 - 8 March 2010 through 12 March 2010
ER -