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Log-based architectures for general-purpose monitoring of deployed code
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Source Architectural Support for Programming Languages and Operating Systems archive
Proceedings of the 1st workshop on Architectural and system support for improving software dependability table of contents
San Jose, California
Pages: 63 - 65  
Year of Publication: 2006
ISBN:1-59593-576-2
Authors
Shimin Chen  Intel Research Pittsburgh
Babak Falsafi  Carnegie Mellon University
Phillip B. Gibbons  Intel Research Pittsburgh
Michael Kozuch  Intel Research Pittsburgh
Todd C. Mowry  Intel Research Pittsburgh and Carnegie Mellon University
Radu Teodorescu  Intel Research Pittsburgh and UIUC
Anastassia Ailamaki  Carnegie Mellon University
Limor Fix  Intel Research Pittsburgh
Gregory R. Ganger  Carnegie Mellon University
Bin Lin  Intel Research Pittsburgh and Northwestern
Steven W. Schlosser  Intel Research Pittsburgh
Publisher
ACM  New York, NY, USA
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ABSTRACT

Runtime monitoring tools are invaluable for detecting various types of bugs, in both sequential and multi-threaded programs. However, these tools often slow down the monitored program by an order of magnitude or more [4], implying that the tools are ill-suited for always-on monitoring of deployed code. Fortunately, the emergence of chip multiprocessors as a dominant computing platform means that resources are available on-chip to assist in monitoring tasks. In this brief note, we advocate Log-Based Architectures (LBA) that exploit such on-chip resources in order to dramatically reduce the overhead of runtime program monitoring. Specifically, we propose adding hardware support for logging a main program's trace and delivering it to another (otherwise idle) processing core for inspection. A life-guard program running on this other core executes the desired monitoring task.


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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S. Chen, B. Falsafi, P. B. Gibbons, M. Kozuch, T. C. Mowry, R. Teodorescu, A. Ailamaki, L. Fix, G. R. Ganger, and S. W. Schlosser. Logs and lifeguards: Accelerating dynamic program monitoring. Technical Report IRP-TR-06-05, Intel Research Pittsburgh, May 2006.
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N. Nethercote. Dynamic Binary Analysis and Instrumentation. PhD thesis, University of Cambridge, Nov. 2004. http://valgrind.org.
 
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J. Newsome and D. Song. Dynamic taint analysis for automatic detection, analysis, and signature generation of exploits on commodity software. In NDSS, 2005.
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Collaborative Colleagues:
Shimin Chen: colleagues
Babak Falsafi: colleagues
Phillip B. Gibbons: colleagues
Michael Kozuch: colleagues
Todd C. Mowry: colleagues
Radu Teodorescu: colleagues
Anastassia Ailamaki: colleagues
Limor Fix: colleagues
Gregory R. Ganger: colleagues
Bin Lin: colleagues
Steven W. Schlosser: colleagues