Abstract
Graphics processing unit (GPU) virtualization technology enables a single GPU to be shared among multiple virtual machines (VMs), thereby allowing multiple VMs to perform GPU operations simultaneously with a single GPU. Because GPUs exhibit lower resource scalability than central processing units (CPUs), memory, and storage, many VMs encounter resource shortages while running GPU operations concurrently, implying that the VM performing the GPU operation must wait to use the GPU. In this paper, we propose a partial migration technique for general-purpose graphics processing unit (GPGPU) tasks to prevent the GPU resource shortage in a remote procedure call-based GPU virtualization environment. The proposed method allows a GPGPU task to be migrated to another physical server's GPU based on the available resources of the target's GPU device, thereby reducing the wait time of the VM to use the GPU. With this approach, we prevent resource shortages and minimize performance degradation for GPGPU operations running on multiple VMs. Our proposed method can prevent GPU memory shortage, improve GPGPU task performance by up to 14%, and improve GPU computational performance by up to 82%. In addition, experiments show that the migration of GPGPU tasks minimizes the impact on other VMs.
Original language | English |
---|---|
Pages (from-to) | 948-972 |
Number of pages | 25 |
Journal | Software - Practice and Experience |
Volume | 50 |
Issue number | 6 |
DOIs | |
Publication status | Published - 2020 Jun 1 |
Bibliographical note
Funding Information:information Institute for Information & communications Technology Promotion, 2018-0-00480; MSIT, IITP-2018-0-01405This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program (IITP-2018-0-01405) supervised by the IITP(Institute for Information & communications Technology Planning & Evaluation). This work was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (No.2018-0-00480, Developing the edge cloud platform for the real-time services based on the mobility of connected cars).
Funding Information:
This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program (IITP‐2018‐0‐01405) supervised by the IITP(Institute for Information & communications Technology Planning & Evaluation). This work was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (No.2018‐0‐00480, Developing the edge cloud platform for the real‐time services based on the mobility of connected cars).
Publisher Copyright:
© 2020 John Wiley & Sons, Ltd.
Keywords
- GPU Virtualization
- cloud computing
- resource management
- task migration
ASJC Scopus subject areas
- Software