git-lfs(Used to deal with the large files): Refer to such link, https://github.com/git-lfs/git-lfs/releases, find the proper version and install it.
To collect the GPU benchmarks included in this repository, use the followed commands to get them:
git clone https://github.com/captainnotseeingthesea/GPU-Benchmarks-Collection.git
cd GPU-Benchmarks-Collection
git-lfs pull // Due to this repository includes large files exceeding 100M, use this way to pull them
git submodule init
git submodule update
A collection of some GPU benchmarks, including ISPASS-2009, Parboil, Rodinia, Pannotia, Polybench, Lonestar and so on, which can be got from https://github.com/accel-sim/gpu-app-collection. When using these benchmarks, please remember citing the corresponding papers. Some of these papers are listed as follows:
ISPASS-2009: A. Bakhoda, G. L. Yuan, W. W. L. Fung, H. Wong, and T. M. Aamodt,“Analyzing CUDA workloads using a detailed GPU simulator,” in Proceeding of the International Symposium on Performance Analysis of Systems and Software (ISPASS), April 2009, pp. 163-174
Parboil:J. A. Stratton, C. Rodrigues, I.-J. Sung, N. Obeid, L.-W. Chang,N. Anssari, G. D. Liu, and W.-m. W. Hwu, “Parboil: A Revised Benchmark Suite for Scientific and Commercial Throughput Computing,” Center for Reliable and High-Performance Computing, vol. 127, 2012.
Rodinia: S. Che, M. Boyer, J. Meng, D. Tarjan, J. W. Sheaffer, S.-H. Lee, and K. Skadron, “Rodinia: A Benchmark Suite for Heterogeneous Computing,” in Proceedings of the International Symposium on Workload Characterization (IISWC), October 2009, pp. 44-54
Pannotia: S. Che, B. M. Beckmann, S. K. Reinhardt, and K. Skadron, “Pannotia: Understanding Irregular GPGPU Graph Applications,” in IEEE International Symposium on Workload Characterization (IISWC), 2013, pp. 185-195.
Polybench: S. Grauer-Gray, L. Xu, R. Searles, S. Ayalasomayajula, and J. Cavazos, “Auto-tuning a High-Level Language Targeted to GPU Codes,” in Innovative Parallel Computing (InPar), May 2012, pp. 1-10.
Lonestar: M. Burtscher, R. Nasre, and K. Pingali, “A Quantitative Study of Irregular Programs on GPUs,” in Proceedings of the International Symposium on Workload Characterization (IISWC), November 2012, pp. 141-151
This repository includes longstar, which is an irregualar GPU benchmark, which can be got from https://github.com/IntelligentSoftwareSystems/Galois and https://github.com/IntelligentSoftwareSystems/GaloisGPU Include some new benchmarks which are not included by gpu-app-collection/lonestargpu-2.0. If using this benchmark, please cite the following paper: M. Burtscher, R. Nasre, and K. Pingali, “A Quantitative Study of Irregular Programs on GPUs,” in Proceedings of the International Symposium on Workload Characterization (IISWC), November 2012, pp. 141-145
NVIDIA CUDA SDK Code Samples from https://developer.nvidia.com/cudadownloads. NVIDIA Corporation.
PolyBench/GPU 1.0: PolyBench Benchmarks on the GPU using CUDA, OpenCL, and HMPP This Benchmark contains some workloads which are not included by gpu-app-collection/polybench-gpu-1.0
If using this benchmark, please cite the following paper: S. Grauer-Gray, L. Xu, R. Searles, S. Ayalasomayajula, and J. Cavazos, “Auto-tuning a High-Level Language Targeted to GPU Codes,” in Innovative Parallel Computing (InPar), May 2012, pp. 1-10.
Tango: A Deep Neural Network Benchmark Suite for Various Accelerators If using this benchmark, please cite the following paper when you use the benchmark suite. Aajna Karki, Chethan Palangotu Keshava, Spoorthi Mysore Shivakumar, Joshua Skow, Goutam Madhukeshwar Hegde, and Hyeran Jeon "Detailed Characterization of Deep Neural Networks on GPUs and FPGAs," ACM Workshop on General Purpose GPUs (GPGPU), Providence, RI, April 2019