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// Copyright (c) 2018 Gabriel Laberge// Copyright (c) 2017 Zahra Khatami // Copyright (c) 2016 David Pfander//// Distributed under the Boost Software License, Version 1.0. (See accompanying// file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
#include<cstdlib>
Google Summer of Code 2018 : Alternative Smart Executors
Here is my submission for my project Alternative Smart executors. The objective was to study the applications of machine learning on loop level-parallelism. In previous work [0] a classification method have proven to be successful at predicting the best policies for HPX for-each loops. My Google Summer of Code project goal was based on this paper and the work I did is divided into two sections:
-Improving the implementation of machine learning in hpxML
-Comparing Regressions algorithms to classifications algorithms to see which one would be better at predicting the best chunk size for a hpx for loop.
Improving the implementation of machine learning in hpxML