gMig: Efficient GPU Live Migration Optimized by Software Dirty Page for Full Virtualization
This paper introduces gMig, an open-source and practical GPU live migration solution for full virtualization. By taking advantage of the dirty pattern of GPU workloads, gMig presents the One-Shot Pre-Copy combined with the hashing based Software Dirty Page technique to achieve efficient GPU live migration. Particularly, we propose three approaches for gMig: 1) Dynamic Graphics Address Remapping, which parses and manipulates GPU commands to adjust the address mapping to adapt to a different environment after migration, 2) Software Dirty Page, which utilizes a hashing based approach to detect page modification, overcomes the commodity GPU’s hardware limitation, and speeds up the migration by only sending the dirtied pages, 3) One-Shot Pre-Copy, which greatly reduces the rounds of pre-copy of graphics memory. Our evaluation shows that gMig achieves GPU live migration with an average downtime of 302 ms on Windows and 119 ms on Linux. With the help of Software Dirty Page, the number of GPU pages transferred during the downtime is effectively reduced by 80.0%.
Sun 25 MarDisplayed time zone: Eastern Time (US & Canada) change
14:00 - 15:30 | |||
14:00 30mTalk | gMig: Efficient GPU Live Migration Optimized by Software Dirty Page for Full Virtualization Research Papers Jiacheng Ma , Xiao Zheng Intel Corporation, Yaozu Dong Intel Asia-Pacific R&D Ltd, China, Wentai Li Shanghai Jiao Tong University, Zhengwei Qi Shanghai Jiao Tong University, Bingsheng He National University of Singapore, Haibing Guan Shanghai Jiao Tong University | ||
14:30 30mTalk | VM Live Migration At Scale Research Papers Adam Ruprecht Google, Danny Jones Google, Dmitry Shiraev Google, Greg Harmon Google, Maya Spivak Google, Michael Krebs Google, Miche Baker-Harvey Google, Tyler Sanderson Google | ||
15:00 30mTalk | Demon: An Efficient Solution for on-Device MMU Virtualization in Mediated Pass-Through Research Papers Yu Xu Shanghai Jiao Tong University, Jianguo Yao Shanghai Jiao Tong University, Yaozu Dong Intel Asia-Pacific R&D Ltd, China, Kun Tian Intel Corporation, Xiao Zheng Intel Corporation, Haibing Guan Shanghai Jiao Tong University |