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October 2018
Estimating the Empirical Cost Function of Routines with Dynamic Workloads
CGO '14: Proceedings of Annual IEEE/ACM International Symposium on Code Generation and OptimizationPages 230–239https://doi.org/10.1145/2544137.2544143

A crucial aspect in software development is understanding how an application's performance scales as a function of its input data. Estimating the empirical cost function of individual routines of a program can help developers predict the runtime on ...
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tutorial
February 2014
Estimating the Empirical Cost Function of Routines with Dynamic Workloads
CGO '14: Proceedings of Annual IEEE/ACM International Symposium on Code Generation and OptimizationPages 230–239https://doi.org/10.1145/2581122.2544143

A crucial aspect in software development is understanding how an application's performance scales as a function of its input data. Estimating the empirical cost function of individual routines of a program can help developers predict the runtime on ...
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research-article
October 2012
k-Calling context profiling
OOPSLA '12: Proceedings of the ACM international conference on Object oriented programming systems languages and applicationsPages 867–878https://doi.org/10.1145/2384616.2384679

Calling context trees are one of the most fundamental data structures for representing the interprocedural control flow of a program, providing valuable information for program understanding and optimization. Nodes of a calling context tree associate ...
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ACM SIGPLAN Notices: Volume 47 Issue 10
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research-article
June 2012
Input-sensitive profiling
PLDI '12: Proceedings of the 33rd ACM SIGPLAN Conference on Programming Language Design and ImplementationPages 89–98https://doi.org/10.1145/2254064.2254076

In this paper we present a profiling methodology and toolkit for helping developers discover hidden asymptotic inefficiencies in the code. From one or more runs of a program, our profiler automatically measures how the performance of individual routines ...
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ACM SIGPLAN Notices: Volume 47 Issue 6
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