TY - GEN
T1 - LifeGuard
T2 - 56th Annual Design Automation Conference, DAC 2019
AU - Rathore, Vijeta
AU - Chaturvedi, Vivek
AU - Singh, Amit K.
AU - Srikanthan, Thambipillai
AU - Shafique, Muhammad
N1 - Funding Information:
8 Acknowledgement The coauthor Dr. Shafique’s contributions in this work are supported in parts by the German Research Foundation (DFG) as part of the GetSURE project in the scope of SPP-1500 priority program “Dependable Embedded Systems”. References
Publisher Copyright:
© 2019 Association for Computing Machinery.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/6/2
Y1 - 2019/6/2
N2 - Device scaling to subdeca nanometer has pushed device aging as a primary design concern. In manycore systems, inevitable process variation further adds to delay degradation and, coupled with the scalability issues in manycores, makes aging management, while meeting performance demands, a complex problem. LifeGuard is a performance-centric reinforcement learning-based task mapping strategy that leverages the different impact of applications on aging for improving system health. Experimental results, comparing Life- Guard with two state-of-the-art aging optimizing techniques, on a 256-core system, showed that LifeGuard led to improved health for, respectively, 57% and 74% of the cores, and also an enhanced aggregate core frequency.
AB - Device scaling to subdeca nanometer has pushed device aging as a primary design concern. In manycore systems, inevitable process variation further adds to delay degradation and, coupled with the scalability issues in manycores, makes aging management, while meeting performance demands, a complex problem. LifeGuard is a performance-centric reinforcement learning-based task mapping strategy that leverages the different impact of applications on aging for improving system health. Experimental results, comparing Life- Guard with two state-of-the-art aging optimizing techniques, on a 256-core system, showed that LifeGuard led to improved health for, respectively, 57% and 74% of the cores, and also an enhanced aggregate core frequency.
KW - Aging
KW - Manycore systems
KW - Mapping
KW - Negative-bias temperature instability (NBTI)
KW - Reinforcement learning
UR - http://www.scopus.com/inward/record.url?scp=85067814627&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067814627&partnerID=8YFLogxK
U2 - 10.1145/3316781.3317849
DO - 10.1145/3316781.3317849
M3 - Conference contribution
AN - SCOPUS:85067814627
T3 - Proceedings - Design Automation Conference
BT - Proceedings of the 56th Annual Design Automation Conference 2019, DAC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 2 June 2019 through 6 June 2019
ER -