Altis Benchmark Suite

Altis-cxl repository forked from Altis benchmark suite with updates for multiple application running concurrently by synchronizing the demand paging and data transfer.

Altis is a benchmark suite to test the performance and other aspects of systems with Graphics Processing Units (GPUs), developed in SCEA lab at University of Texas at Austin. Altis consists of a collection of GPU applications with differnt performance implications. Altis focuses primarily on Compute Unified Device Architecture (CUDA) computing platform.

Documentaion regarding this project can be found at the Wiki page. The Wiki document contains information regarding Altis setup, installation, usage, and other information.

We are refactoring Altis codebase for better usability and making it more developer-friendly. We made sure the benchmark still compile properly during refactoring so you can still use it. The refactoring involves changing how each benchmark application is used and adding more benchmarks.

Setup

Altis relies on the avaialbility of CUDA and CMake (>= 3.8). Please refer to Environment Setup for how to set up Altis.

Build:

After the environment is setup properly, go to the root directory of Altis, execute:

./setup.sh

For more information regarding building process, please refer to Build for more information.

Run

To run all the benchmarks, simply execute ./runall.sh [number for iteration] script. This will run all the benchmarks with specified iterations and save the results (kernel execution time and data transfer latency) into ./results directory. You can modify runall.sh to change the size of dataset (-s options from the script).

Cite Us

Bibtex is shown below:

@INPROCEEDINGS{9238617,
author={B. {Hu} and C. J. {Rossbach}},
booktitle={2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)},
title={Altis: Modernizing GPGPU Benchmarks},
year={2020},
volume={},
number={},
pages={1-11},
doi={10.1109/ISPASS48437.2020.00011}}

Publication

B. Hu and C. J. Rossbach, "Altis: Modernizing GPGPU Benchmarks," 2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), Boston, MA, USA, 2020, pp. 1-11, doi: 10.1109/ISPASS48437.2020.00011.