A Checkpoint/Restart Scheme for CUDA Programs with Complex Computation States

DOI

10.2991/ijndc.2013.1.4.2How to use a DOI?

Keywords

GPU, CUDA, checkpoint/start, fault tolerance

Abstract

Checkpoint/restart has been an effective mechanism to achieve fault tolerance for many long-running scientific applications. The common approach is to save computation states in memory and secondary storage for execution resumption. However, as the GPU plays a much bigger role in high performance computing, there is no effective checkpoint/restart scheme yet due to the difficulty of the GPU computation state handling. This paper proposes an application-level checkpoint/restart scheme to save and restore GPU computation states in annotated user programs. A pre-compiler and run-time support module are developed to construct and save states in CPU system memory dynamically, whereas secondary storage can be utilized for scalability and long-term fault tolerance. CUDA programs with complicated computation states are supported. State-related variables dissipated in various memory units are collected. Both stack and heap are duplicated at application level for state construction. Experimental results have demonstrated the effectiveness of the proposed scheme.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Hai Jiang
AU  - Yulu Zhang
AU  - Jeff Jennes
AU  - Kuan-Ching Li
PY  - 2013
DA  - 2013/11/01
TI  - A Checkpoint/Restart Scheme for CUDA Programs with Complex Computation States
JO  - International Journal of Networked and Distributed Computing
SP  - 196
EP  - 212
VL  - 1
IS  - 4
SN  - 2211-7946
UR  - https://doi.org/10.2991/ijndc.2013.1.4.2
DO  - 10.2991/ijndc.2013.1.4.2
ID  - Jiang2013
ER  -