LonestarGPU is a collection of widely-used real-world applications that
exhibit irregular behavior.
This work is done in collaboration with Texas State University, San Marcos, USA
IMPORTANT: LonestarGPU 6.0 supports latest CUDA versions and compute capabilities. You are strongly encouraged to upgrade to version 6.0.
2020-05 LonestarGPU<firstname.lastname@example.org> * Version 6.0 * Upgraded to support latest CUDA versions and compute capabilities * Previous versions of LonestarGPU were hosted as stand-alone git-hub repositry. This version has been integrated with the Galois git hub repository. Accordingly, the version number has been revised to 6.0 instead of 5.0 2019-05 LonestarGPU<email@example.com> * Version 4.0 * New benchmarks added: CC (Connected Components), PR (PageRank), TC (Triangle Counting), and MIS (Maximal Independent Set) * Faster version of BFS and SSSP are generated by IrGL compiler * All the new implementations produce output for easy verification 2018-07 LonestarGPU<firstname.lastname@example.org> * Version 3.0 * New implementations of BFS, SSSP, DMR, MST, SP, and SGD * Faster version of BFS, SSSP, DMR, and MST are generated by IrGL compiler * All the new implementations produce output for easy verification * SGD is added to the benchmark 2013-09-03 LonestarGPU<email@example.com> * version 2.0 * Breadth-First Search bug fix on computing amount of work per thread. * Barnes-Hut uses diameter instead of radius. * Delaunay Mesh Refinement bug fix about reading input * Minimum Spanning Tree uses union-find * Header fix for MAC and FreeBSD * Update to CudaSM2Cores 2013-02-01 LonestarGPU<firstname.lastname@example.org> * version 1.0 * uses common code base * Barnes Hut: bug fix, additional optimizations, and Kepler support added * Points-to Analysis: 4.x compatibility * inputs can be downloaded with "make inputs" 2013-01-16 LonestarGPU <email@example.com> * version 0.9 * added Breadth-First Search * added Barnes-Hut N-Body Simulation * added Delaunay Mesh Refinement * added Minimum Spanning Tree * added Points-to Analysis * added Single-Source Shortest Paths * added Survey Propagation
Related publicationIf you find this software useful in academic work, please acknowledge LonestarGPU and cite the following publication:
A Quantitative Study of Irregular Programs on GPUs
Martin Burtscher, Rupesh Nasre, Keshav Pingali
IEEE International Symposium on Workload Characterization (IISWC) 2012
This software is released under the BSD-3-clause license.
Galois, a framework to exploit amorphous data-parallelism in irregular programs. Copyright (C) 2018, The University of Texas at Austin. All rights reserved. UNIVERSITY EXPRESSLY DISCLAIMS ANY AND ALL WARRANTIES CONCERNING THIS SOFTWARE AND DOCUMENTATION, INCLUDING ANY WARRANTIES OF MERCHANTABILITY, FITNESS FOR ANY PARTICULAR PURPOSE, NON-INFRINGEMENT AND WARRANTIES OF PERFORMANCE, AND ANY WARRANTY THAT MIGHT OTHERWISE ARISE FROM COURSE OF DEALING OR USAGE OF TRADE. NO WARRANTY IS EITHER EXPRESS OR IMPLIED WITH RESPECT TO THE USE OF THE SOFTWARE OR DOCUMENTATION. Under no circumstances shall University be liable for incidental, special, indirect, direct or consequential damages or loss of profits, interruption of business, or related expenses which may arise from use of Software or Documentation, including but not limited to those resulting from defects in Software and/or Documentation, or loss or inaccuracy of data of any kind.
Note that LonestarGPU 2.0 also includes code from NVIDIA. Please see the individual files for license information.