In-place Parallel Super Scalar Samplesort (IPS⁴o)
This is the implementation of the algorithm presented in the eponymous paper, which contains an in-depth description of its inner workings, as well as an extensive experimental performance evaluation. Here's the abstract:
We present a sorting algorithm that works in-place, executes in parallel, is cache-efficient, avoids branch-mispredictions, and performs work O(n log n) for arbitrary inputs with high probability. The main algorithmic contributions are new ways to make distribution-based algorithms in-place: On the practical side, by using coarse-grained block-based permutations, and on the theoretical side, we show how to eliminate the recursion stack. Extensive experiments show that our algorithm IPS⁴o scales well on a variety of multi-core machines. We outperform our closest in-place competitor by a factor of up to 3. Even as a sequential algorithm, we are up to 1.5 times faster than the closest sequential competitor, BlockQuicksort.
This repository is deprecated! The current version of IPS⁴o is published at https://github.com/ips4o/ips4o. You may also want to check out our prototypical implementation of In-place Parallel Super Scalar Radix Sort (IPS²Ra) at https://github.com/ips4o/ips2ra. IPS²Ra applies the in-place approach of IPS⁴o to radix sort. The new repositories support the CMake build system.
#include "ips4o.hpp"// sort sequentially ips4o::sort(begin, end[, comparator])
// sort in parallel (uses OpenMP if available, std::thread otherwise) ips4o::parallel::sort(begin, end[, comparator])
Make sure to compile with C++14 support. Currently, the code does not compile on Windows.
For the parallel algorithm, you need to enable either OpenMP (
-fopenmp) or C++ threads (e.g.,
-pthread). You also need a CPU that supports 16-byte compare-and-exchange instructions. If you get undefined references to
__atomic_fetch_add_16, either set your CPU correctly (e.g.,
-march=native), enable the instructions explicitly (
-mcx16), or try linking against GCC's libatomic (
-latomic).
IPS⁴o is free software provided under the BSD 2-Clause License described in the LICENSE file. If you use IPS⁴o in an academic setting please cite the eponymous paper using the BibTeX entry
@InProceedings{axtmann2017, author = {Michael Axtmann and Sascha Witt and Daniel Ferizovic and Peter Sanders}, title = {{In-Place Parallel Super Scalar Samplesort (IPSSSSo)}}, booktitle = {25th Annual European Symposium on Algorithms (ESA 2017)}, pages = {9:1--9:14}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, year = {2017}, volume = {87}, publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik}, doi = {10.4230/LIPIcs.ESA.2017.9}, }