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Statistical performance tuning of parallel Monte Carlo ocean color simulations Abstract:Statistical performance tuning of a parallel Monte Carlo (MC) radiative transfer code for ocean color (OC) applications is presented. A low observed-to-peak performance ratio due to highly sparse computations is compensated by online and offline tuning techniques based on a statistical indicator of products accuracy. Run-time adaptive control employs the accuracy indicator to set up two complementary tuning criteria: one general to MC computations and the other specific to OC applications. The same accuracy indicator is also used for pre-execution tuning of a threshold parameter. Numerical simulations of real case scenarios showed that the proposed methods consistently led to faster runs, while satisfying application accuracy requirements. Specifically, speed-ups range from 2.17 to 7.44 times when compared with the un-optimized version of the MC code. The applied techniques are orthogonal to parallelization, so that the reported performance gains are further amplified by parallel speed-ups. URL: http://dx.doi.org/10.1109/PDCAT.2012.125 @ The 13th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT'12), Beijing, China Publisher: IEEE Computer Society ( United States ) Pages: 761 to 766 Date: December, 2012 Authors:
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