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Iterative Optimization for the Data Center

By Yang Chen, Lieven Eeckhout, Olivier Temam and Chengyong Wu

Abstract

Iterative optimization is a simple but powerful approach that searches for the best possible combination of compiler optimizations for a given workload. However, each program, if not each data set, potentially favors a different combination. As a result, iterative optimization is plagued by several practical issues that prevent it from being widely used in practice: a large number of runs are required for finding the best combination; the process can be data set dependent; and the exploration process incurs significant overhead that needs to be compensated for by performance benefits. Therefore, while iterative optimization has been shown to have significant performance potential, it is seldomly used in production compilers. In this paper, we propose Iterative Optimization for the Data Center (IODC): we show that servers and data centers offer a contex

Topics: Categories and Subject Descriptors D.3.4 [Processors, Compilers General Terms Design, Performance Keywords iterative optimization, compiler, MapReduce, server, data center
Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.308.4869
Provided by: CiteSeerX
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