By Omer Rana, Giandomenico Spezzano, Michael Gerndt, Daniel S. Katz (auth.), Pasqua D’Ambra, Mario Guarracino, Domenico Talia (eds.)
This booklet constitutes the refereed complaints of the sixteenth overseas Euro-Par convention held in Ischia, Italy, in August/September 2010. The ninety revised complete papers awarded have been conscientiously reviewed and chosen from 256 submissions. The papers are equipped in topical sections on aid instruments and environments; functionality prediction and evaluate; scheduling and load-balancing; excessive functionality architectures and compilers; parallel and disbursed facts administration; grid, cluster and cloud computing; peer to look computing; allotted structures and algorithms; parallel and disbursed programming; parallel numerical algorithms; multicore and manycore programming; idea and algorithms for parallel computation; excessive functionality networks; and cellular and ubiquitous computing.
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Extra resources for Euro-Par 2010 - Parallel Processing: 16th International Euro-Par Conference, Ischia, Italy, August 31 - September 3, 2010, Proceedings, Part I
Number of subsets for sample sort). 1 Tuning Steps We ﬁrst split those parameters into orthogonal groups with no or few dependencies, then look for the best parameter set for each group. Fig. 1 illustrates the whole work ﬂow of parameter tuning: 1. We tune the register sort threshold and register sort algorithm only once, then we use the parameter set as building blocks for other sorting algorithms. Automated Tuning in Parallel Sorting on Multi-core Architectures 19 START Generate input Tune register sort threshold Tune register sort algorithm Generate input Select # of threads Y Y More input to tune?
Many more parallel sorting algorithms were proposed later on, including parallel version of radix sort and quick sort , a variant of quicksort called hyperquicksort, and other algorithms such as smooth sort, column sort, and parallel merge sort. In recent year, sorting algorithms have been extended to exploit the SIMD and multicore capability of modern processors, including GPUs, Cell, and others. Bitonic sort is implemented using a sorting network without unpredictable branches, making it well suited for SIMD processors.
As the number of threads increases, sample sort is chosen by our library. 7 Conclusions In this paper, we presented automated tuning for parallel sorting algorithms on modern multi-core architectures. We discussed several practical parameter tuning methodologies for parallel sorting considering both the characteristics of architectures and input data sets. Particularly, thread aﬃnity was taken into account on multi-core architectures. We have built an parallel sorting library based on parameter tuning and machine learning techniques of artiﬁcial neural network.
Euro-Par 2010 - Parallel Processing: 16th International Euro-Par Conference, Ischia, Italy, August 31 - September 3, 2010, Proceedings, Part I by Omer Rana, Giandomenico Spezzano, Michael Gerndt, Daniel S. Katz (auth.), Pasqua D’Ambra, Mario Guarracino, Domenico Talia (eds.)