Analysis of GPGPU Programs for Data-race and Barrier Divergence

Santonu Sarkar, Prateek Kandelwal, Soumyadip Bandyopadhyay, Holger Giese

2018

Abstract

Todays business and scientific applications have a high computing demand due to the increasing data size and the demand for responsiveness. Many such applications have a high degree of parallelism and GPGPUs emerge as a fit candidate for the demand. GPGPUs can offer an extremely high degree of data parallelism owing to its architecture that has many computing cores. However, unless the programs written to exploit the architecture are correct, the potential gain in performance cannot be achieved. In this paper, we focus on the two important properties of the programs written for GPGPUs, namely i) the data-race conditions and ii) the barrier divergence. We present a technique to identify the existence of these properties in a CUDA program using a static property verification method. The proposed approach can be utilized in tandem with normal application development process to help the programmer to remove the bugs that can have an impact on the performance and improve the safety of a CUDA program.

Paper Citation

in Harvard Style

Kandelwal P., Bandyopadhyay S. and Giese H. (2018). Analysis of GPGPU Programs for Data-race and Barrier Divergence.In Proceedings of the 13th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-320-9, pages 460-471. DOI: 10.5220/0006834904600471

in Bibtex Style

@conference{icsoft18,
author={Prateek Kandelwal and Soumyadip Bandyopadhyay and Holger Giese},
title={Analysis of GPGPU Programs for Data-race and Barrier Divergence},
booktitle={Proceedings of the 13th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2018},
pages={460-471},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006834904600471},
isbn={978-989-758-320-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - Analysis of GPGPU Programs for Data-race and Barrier Divergence
SN - 978-989-758-320-9
AU - Kandelwal P.
AU - Bandyopadhyay S.
AU - Giese H.
PY - 2018
SP - 460
EP - 471
DO - 10.5220/0006834904600471