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DOE OSTI · 1074171

An algorithm for online optimization of accelerators

Huang, Xiaobiao·Corbett, Jeff·Safranek, James·Wu, Juhao
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Abstract

We developed a general algorithm for online optimization of accelerator performance, i.e., online tuning, using the performance measure as the objective function. This method, named robust conjugate direction search (RCDS), combines the conjugate direction set approach of Powell's method with a robust line optimizer which considers the random noise in bracketing the minimum and uses parabolic fit of data points that uniformly sample the bracketed zone. Moreover, it is much more robust against noise than traditional algorithms and is therefore suitable for online application. Simulation and experimental studies have been carried out to demonstrate the strength of the new algorithm.

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43 PARTICLE ACCELERATORS97 MATHEMATICS AND COMPUTINGAcceleratorsACCPHYACCSYSCOMPComputing

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Huang, Xiaobiao, Corbett, Jeff, Safranek, James, Wu, Juhao. 2013-10-01. An algorithm for online optimization of accelerators. https://doi.org/10.1016/j.nima.2013.05.046

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