Abstract
The presence of FPGAS in data centers has been growing due to their superior performance as accelerators. Thermal management, particularly battling the cooling cost in these high performance systems, is a primary concern. Introduction of new heterogeneous components only adds further complexities to thermal modeling and management. The thermal behavior of multi-FPGA systems deployed within large compute clusters is little explored. In this paper, we first show that the thermal behaviors of different FPGAS of the same generation can vary due to their physical locations in a rack and process variation, even though they are running the same tasks. We present a machine learning based model to capture the thermal behavior of a multi-node FPGA cluster. We then propose to mitigate thermal variation and hotspots across the cluster by proactive task placement guided by our thermal model. Our experiments show that through proper placement of tasks on the multi-FPGA system, we can reduce the peak temperature by up to 11.50°C with no impact on performance.
Original language | English (US) |
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Title of host publication | Proceedings - 2018 IEEE 36th International Conference on Computer Design, ICCD 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 537-544 |
Number of pages | 8 |
ISBN (Electronic) | 9781538684771 |
DOIs | |
State | Published - Jan 16 2019 |
Event | 36th International Conference on Computer Design, ICCD 2018 - Orlando, United States Duration: Oct 7 2018 → Oct 10 2018 |
Publication series
Name | Proceedings - 2018 IEEE 36th International Conference on Computer Design, ICCD 2018 |
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Conference
Conference | 36th International Conference on Computer Design, ICCD 2018 |
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Country/Territory | United States |
City | Orlando |
Period | 10/7/18 → 10/10/18 |
Funding
ACKNOWLEDGMENT Results presented in this paper were obtained using the Chameleon testbed supported by the National Science Foundation.
Keywords
- HPC
- Task Placement
- Thermal Modeling
ASJC Scopus subject areas
- Computer Networks and Communications
- Hardware and Architecture
- Safety, Risk, Reliability and Quality