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Process variation characterization of chip-level multiprocessors
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 46th Annual Design Automation Conference table of contents
San Francisco, California
SESSION: Hardware authentication, characterization and trusted design table of contents
Pages 694-697  
Year of Publication: 2009
ISBN:978-1-60558-497-3
Authors
Lide Zhang  Northwestern University, Evanston, IL
Lan S. Bai  University of Michigan, Ann Arbor, MI
Robert P. Dick  University of Michigan, Ann Arbor, MI
Li Shang  University of Colorado, Boulder, CO
Russ Joseph  Northwestern University, Evanston, IL
Sponsors
EDAC : Electronic Design Automation Consortium
SIGDA: ACM Special Interest Group on Design Automation
IEEE-CAS : Circuits & Systems
Publisher
ACM  New York, NY, USA
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ABSTRACT

Within-die variation in leakage power consumption is substantial and increasing for chip-level multiprocessors (CMPs) and multiprocessor systems-on-chip. Dealing with this problem via conservative assumptions is sub-optimal. Instead, operating systems may adapt task assignment and power management decisions to the variable characteristics of cores, improving system-wide power consumption and performance. Researchers have proposed such adaptation techniques. However, they rely on knowledge of CMP process variation (PV) maps. These maps are not provided by processor vendors, providing them would impose additional cost during the testing process, and static maps would not permit adaptation to aging effects. Further progress on developing and validating PV aware control techniques for CMPs requires access to PV maps for real processors. We present an online technique to extract the PV maps of CMPs. Potentially automatic temperature measurements with built-in on-die sensors during the execution of characterization workloads are used to determine variation in leakage power consumption. The proposed technique is applied to real CMPs, and the resulting PV maps are used within a PV aware task assignment and scheduling algorithm.


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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