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Published byChristina Madsen Modified over 5 years ago
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Calpa: A Tool for Automating Dynamic Compilation
Markus Mock, Mark Berryman, Craig Chambers, and Susan J. Eggers University of Washington
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Outline Motivation Overview of DyC Calpa System Experimental Results
Conclusion Discussion
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Motivation Run time constants Optimizations Specialized code regions
Constant propagation Loop unrolling Specialized code regions Dynamic optimization > run-time cost
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DyC: Dynamic Compiler Annotation directed run time specialization
Manual annotation requires Good knowledge of application run-time behavior Run time costs? Legal annotation? X = 3 /* run time constant (but not really…) */
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Motivation for Calpa Manual annotation is difficult, and often becomes bottleneck Automated annotation = Calpa
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Calpa Combines program analysis and profile information to automatically derive annotations Cost / Benefit Model predicts effect of annotation Implemented with SUIF
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Experimental Results Small and medium applications annotated
Instrumented program size: x 8-14 Run time of instrumented executable: x 2 – 4 orders of magnitude (x = un-instrumented application)
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Conclusion Calpa automates annotation process for dynamic compilation
It is faster and produces better annotations than manual process
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Discussion Dynamic Compiler needs more work
Too slow for actual gains Run time constants can boost ILP and memory prefetching What about phase oriented optimizations?
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