TY - JOUR
T1 - Aging-Aware Energy-Efficient Task Deployment of Heterogeneous Multicore Systems
AU - Chen, Yu Guang
AU - Wang, Chieh Shih
AU - Lin, Ing Chao
AU - Chen, Zheng Wei
AU - Schlichtmann, Ulf
N1 - Publisher Copyright:
© 1982-2012 IEEE.
PY - 2024/5/1
Y1 - 2024/5/1
N2 - Heterogeneous multicore systems, which consist of high-performance and power-efficient cores, are emerging to satisfy the various demands on performance and power consumption. On the other hand, as CMOS technology continues to shrink in size, the aging effect, which can cause performance degradation or timing failures, has become a non-negligible threat to lifetime reliability. To overcome the challenges under the aging effect, various approaches have been proposed in previous studies. Most previous studies, however, did not consider the different characteristics of big and little cores. In addition, most of them do not consider critical tasks with the strict timing requirements present in real-time applications, resulting in early system failure. Therefore, considering different characteristics of cores and the presence of critical tasks, we propose an aging-aware task deployment framework for real-time systems. In this framework, for high-performance big cores, we propose a novel asymmetric aging-aware strategy. This strategy finds an energy-efficient task-to-core assignment to reserve some healthy cores at the early system life stage. The reserved cores are kept idle with the lowest voltage and can execute critical tasks at the late system life stage, extending the system lifetime. Meanwhile, the nonreserved cores use lower voltages to execute tasks, reducing the aging effect. For energy-efficient little cores, we adopt the symmetric aging-aware strategy to balance out the aging effect of each little core. With a balanced aging effect, the utilization of little cores is improved. In addition, we propose voltage/frequency boosting and task migration techniques to increase the number of cores that can meet the task timing constraints. Compared to the state of the art, the proposed framework can achieve 1.10× lifetime improvement and 5% energy reduction.
AB - Heterogeneous multicore systems, which consist of high-performance and power-efficient cores, are emerging to satisfy the various demands on performance and power consumption. On the other hand, as CMOS technology continues to shrink in size, the aging effect, which can cause performance degradation or timing failures, has become a non-negligible threat to lifetime reliability. To overcome the challenges under the aging effect, various approaches have been proposed in previous studies. Most previous studies, however, did not consider the different characteristics of big and little cores. In addition, most of them do not consider critical tasks with the strict timing requirements present in real-time applications, resulting in early system failure. Therefore, considering different characteristics of cores and the presence of critical tasks, we propose an aging-aware task deployment framework for real-time systems. In this framework, for high-performance big cores, we propose a novel asymmetric aging-aware strategy. This strategy finds an energy-efficient task-to-core assignment to reserve some healthy cores at the early system life stage. The reserved cores are kept idle with the lowest voltage and can execute critical tasks at the late system life stage, extending the system lifetime. Meanwhile, the nonreserved cores use lower voltages to execute tasks, reducing the aging effect. For energy-efficient little cores, we adopt the symmetric aging-aware strategy to balance out the aging effect of each little core. With a balanced aging effect, the utilization of little cores is improved. In addition, we propose voltage/frequency boosting and task migration techniques to increase the number of cores that can meet the task timing constraints. Compared to the state of the art, the proposed framework can achieve 1.10× lifetime improvement and 5% energy reduction.
KW - Aging degradation
KW - asymmetric aging
KW - energy
KW - heterogeneous multicore system
KW - lifetime
KW - negative bias temperature instability (NBTI)
KW - reliability
UR - http://www.scopus.com/inward/record.url?scp=85174808343&partnerID=8YFLogxK
U2 - 10.1109/TCAD.2023.3323163
DO - 10.1109/TCAD.2023.3323163
M3 - 期刊論文
AN - SCOPUS:85174808343
SN - 0278-0070
VL - 43
SP - 1580
EP - 1593
JO - IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
JF - IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IS - 5
ER -