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Slipstream processors: improving both performance and fault tolerance
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Source ACM SIGPLAN Notices archive
Volume 35 ,  Issue 11  (November 2000) table of contents
Pages: 257 - 268  
Year of Publication: 2000
ISSN:0362-1340
Authors
Karthik Sundaramoorthy  North Carolina State University, Department of Electrical and Computer Engineering, Engineering Graduate Research Center, Campus Box 7914, Raleigh, NC
Zach Purser  North Carolina State University, Department of Electrical and Computer Engineering, Engineering Graduate Research Center, Campus Box 7914, Raleigh, NC
Eric Rotenberg  North Carolina State University, Department of Electrical and Computer Engineering, Engineering Graduate Research Center, Campus Box 7914, Raleigh, NC
Publisher
ACM  New York, NY, USA
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ABSTRACT

Processors execute the full dynamic instruction stream to arrive at the final output of a program, yet there exist shorter instruction streams that produce the same overall effect. We propose creating a shorter but otherwise equivalent version of the original program by removing ineffectual computation and computation related to highly-predictable control flow. The shortened program is run concurrently with the full program on a chip multiprocessor or simultaneous multithreaded processor, with two key advantages:1) Improved single-program performance. The shorter program speculatively runs ahead of the full program and supplies the full program with control and data flow outcomes. The full program executes efficiently due to the communicated outcomes, at the same time validating the speculative, shorter program. The two programs combined run faster than the original program alone. Detailed simulations of an example implementation show an average improvement of 7% for the SPEC95 integer benchmarks.2) Fault tolerance. The shorter program is a subset of the full program and this partial-redundancy is transparently leveraged for detecting and recovering from transient hardware faults.


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:
Karthik Sundaramoorthy: colleagues
Zach Purser: colleagues
Eric Rotenberg: colleagues