Dynamic voltage and frequency scaling for neuromorphic many-core systems
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-review
Contributors
Abstract
We present a dynamic voltage and frequency scaling technique within SoCs for per-core power management: the architecture allows for individual, self triggered performance-level scaling of the processing elements (PEs) within less than 100ns. This technique enables each core to adjust its local supply voltage and frequency depending on its current computational load. A test chip has been implemented in 28nm CMOS technology, as prototype of the SpiNNaker2 neuromorphic many core system, containing 4 PEs which are operational within the range of 1.1V down to 0.7V at frequencies from 666MHz down to 100MHz; the effectiveness of the power management technique is demonstrated using a standard benchmark from the application domain. The particular domain area of this application specific processor is real-time neuromorphics. Using a standard benchmark - the synfire chain - we show that the total power consumption can be reduced by 45%, with 85% baseline power reduction and a 30% reduction of energy per neuron and synapse computation, all while maintaining biological real-time operation.
Details
Original language | English |
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Title of host publication | 2017 IEEE International Symposium on Circuits and Systems (ISCAS) |
Place of Publication | Baltimore |
Publisher | IEEE Xplore |
ISBN (electronic) | 978-1-4673-6853-7 |
ISBN (print) | 978-1-5090-1427-9 |
Publication status | Published - 25 Sept 2017 |
Peer-reviewed | Yes |
Publication series
Series | IEEE International Symposium on Circuits and Systems (ISCAS) |
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ISSN | 0271-4302 |
Conference
Title | IEEE International Symposium on Circuits and Systems 2017 |
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Abbreviated title | ISCAS 2017 |
Conference number | 50 |
Duration | 28 - 31 May 2017 |
City | Baltimore |
Country | United States of America |
External IDs
ORCID | /0000-0002-6286-5064/work/142240637 |
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Keywords
ASJC Scopus subject areas
Keywords
- DVFS, MPSoC, neuromorphic computing, power management, SpiNNaker2, synfire chain