Profiling a Many-core Neuromorphic Platform

Indar Sugiarto, Luis A. Plana, Steven Temple, Basabdatta Sen Bhattacharya, Stephen Furber, Patrick Camilleri

Research output: Contribution to conferencePaperpeer-review

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Abstract

This paper presents a unified profiling platform for a many-core machine that gives realtime information about the current states of the system. Such information are valuable for observation and evaluation of running programs on the machine, as well as the health status of the machine itself. The information from the profiler can also be used for tuning the system’s kernel operational parameters to maintain its performance and reliability. In our work, the profiler framework is developed for SpiNNaker, a many-core neuromorphic platfrom. The profiler framework provides realtime information such as power consumption, chips temperature, processors frequency, cores utilization, and network connectivity. Many researchers and institutions have been using SpiNNaker not only for simulating spiking neural networks, but also for general purpose and energy-aware computing. Therefore, it is important to provide a reliable and comprehensive profiling platform for helping SpiNNaker users in developing their program.
Original languageEnglish
Number of pages6
Publication statusPublished - 21 Sep 2017
EventThe 11th IEEE International Conference Application of Information and Communication Technologie - Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russian Federation
Duration: 20 Sep 201722 Sep 2017
Conference number: 41663
http://www.aict.info

Conference

ConferenceThe 11th IEEE International Conference Application of Information and Communication Technologie
Abbreviated titleAICT2017
Country/TerritoryRussian Federation
CityMoscow
Period20/09/1722/09/17
Internet address

Keywords

  • Many-core processors
  • SpiNNaker
  • Neuromorphic

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