Multi-Tier GPU Virtualization for Deep Learning in Cloud-Edge Systems
Author:
Affiliation:
1. Queen's University Belfast, Belfast, United Kingdom
2. University of St Andrews, St Andrews, United Kingdom
3. Universitat de València, València, Spain
Funder
ETRI-Korea
NRF-Korea
IITP-Korea
MSIT-Korea
AFOSR-USA
Innovate U.K., PwC, VIAVI, UKRI- Horizon, DCMS
Defence Science and Technology Laboratory
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computational Theory and Mathematics,Hardware and Architecture,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/71/10132303/10122723.pdf?arnumber=10122723
Reference46 articles.
1. Real-time edge framework (RTEF): task scheduling and realisation
2. Hetero-Edge: Orchestration of Real-time Vision Applications on Heterogeneous Edge Clouds
3. Online Placement of Multi-Component Applications in Edge Computing Environments
4. A Hardware and Software Task-Scheduling Framework Based on CPU+FPGA Heterogeneous Architecture in Edge Computing
5. A full GPU virtualization solution with mediated pass-through;tian;Proc USENIX Conf USENIX Annu Tech Conf,2014
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