Refereed article in conference proceedings (A4)

Approximation for Run-time Power Management




List of AuthorsAnil Kanduri, Mohammad-Hashem Haghbayan, Amir M. Rahmani, Pasi Liljeberg

EditorsNo available

Conference nameIEEE International Symposium on Circuits and Systems

Publication year2018

JournalIEEE International Symposium on Circuits and Systems. Proceedings

Book title *2018 IEEE International Symposium on Circuits and Systems (ISCAS)

Journal name in source2018 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS)

Journal acronymIEEE INT SYMP CIRC S

Title of seriesIEEE International Symposium on Circuits and Systems. Proceedings

Volume number2018

Number of pages4

ISBN978-1-5386-4882-7

ISSN0271-4302

eISSN2379-447X

DOIhttp://dx.doi.org/10.1109/ISCAS.2018.8351841


Abstract
Performance and energy efficiency of multi-core and many-core systems are restricted by increasing power densities and/or limited energy resources. Maximizing performance while minimizing power and energy consumption becomes challenging with emerging workloads. Approximate computing is an alternative solution that offers the required performance and energy gains, leveraging inherent error resilience of specific application domains. Dynamic power management using approximation as another knob can maximize performance and energy efficiency within fixed power budgets. Disciplined tuning of approximation along with other traditional power knobs requires efficient run-time resource management techniques. We present our strategy for using approximation as another knob for tuning the performance loss incurred in power actuation in many-core systems, which is also portable for heterogeneous multi-core systems.


Last updated on 2021-24-06 at 10:11