CheCUDA: A Checkpoint/Restart Tool for CUDA Applications

Abstract—In this paper, a tool named CheCUDA is designed to checkpoint CUDA applications that use GPUs as accelerators. As existing checkpoint/restart implementations do not support checkpointing the GPU status, CheCUDA hooks a part of basic CUDA driver API calls in order to record the status changes on the main memory. At checkpointing, CheCUDA stores the status changes in a file after copying all necessary data in the video memory to the main memory and then disabling the CUDA runtime. At restarting, CheCUDA reads the file, re-initializes the CUDA runtime, and recovers the resources on GPUs so as to restart from the stored status. This paper demonstrates that a prototype implementation of CheCUDA can correctly checkpoint and restart a CUDA application written with basic APIs. This also indicates that CheCUDA can migrate a process from one PC to another even if the process uses a GPU. Accordingly, CheCUDA is useful not only to enhance the dependability of CUDA applications but als...

• Type: Conference
• Year: 2009
• Where: PDCAT
• Authors: Hiroyuki Takizawa, Katsuto Sato, Kazuhiko Komatsu, Hiroaki Kobayashi
• Keywords: CUDA, Cuda Applications, CUDA Runtime, Distributed And Parallel Computing, PDCAT 2009