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Software thermal management of dram memory for multicore systems
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Joint International Conference on Measurement and Modeling of Computer Systems archive
Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems table of contents
Annapolis, MD, USA
SESSION: Energy table of contents
Pages 337-348  
Year of Publication: 2008
ISBN:978-1-60558-005-0
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Authors
Jiang Lin  Iowa State University, Ames, IA, USA
Hongzhong Zheng  University of Illinois at Chicago, Chicago, IL, USA
Zhichun Zhu  University of Illinois at Chicago, Chicago, IL, USA
Eugene Gorbatov  Intel Corp., Hillsboro, OR, USA
Howard David  Intel Corp., Hillsboro, IL, USA
Zhao Zhang  Iowa State University, Ames, IA, USA
Sponsors
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Thermal management of DRAM memory has become a critical issue for server systems. We have done, to our best knowledge, the first study of software thermal management for memory subsystem on real machines. Two recently proposed DTM (Dynamic Thermal Management) policies have been improved and implemented in Linux OS and evaluated on two multicore servers, a Dell PowerEdge 1950 server and a customized Intel SR1500AL server testbed. The experimental results first confirm that a system-level memory DTM policy may significantly improve system performance and power efficiency, compared with existing memory bandwidth throttling scheme. A policy called DTM-ACG (Adaptive Core Gating) shows performance improvement comparable to that reported previously. The average performance improvements are 13.3% and 7.2% on the PowerEdge 1950 and the SR1500AL (vs. 16.3% from the previous simulation-based study), respectively. We also have surprising findings that reveal the weakness of the previous study: the CPU heat dissipation and its impact on DRAM memories, which were ignored, are significant factors. We have observed that the second policy, called DTM-CDVFS (Coordinated Dynamic Voltage and Frequency Scaling), has much better performance than previously reported for this reason. The average improvements are 10.8% and 15.3% on the two machines (vs. 3.4% from the previous study), respectively. It also significantly reduces the processor power by 15.5% and energy by 22.7% on average.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Jiang Lin: colleagues
Hongzhong Zheng: colleagues
Zhichun Zhu: colleagues
Eugene Gorbatov: colleagues
Howard David: colleagues
Zhao Zhang: colleagues