Paper Info
Title
GLoop: an event-driven runtime for consolidating GPGPU applications.
Abstract
Graphics processing units (GPUs) have become an attractive platform for general-purpose computing (GPGPU) in various domains. Making GPUs a time-multiplexing resource is a key to consolidating GPGPU applications (apps) in multi-tenant cloud platforms. However, advanced GPGPU apps pose a new challenge for consolidation. Such highly functional GPGPU apps, referred to as GPU eaters, can easily monopolize a shared GPU and starve collocated GPGPU apps. This paper presents GLoop, which is a software runtime that enables us to consolidate GPGPU apps including GPU eaters. GLoop offers an event-driven programming model, which allows GLoop-based apps to inherit the GPU eaters' high functionality while proportionally scheduling them on a shared GPU in an isolated manner. We implemented a prototype of GLoop and ported eight GPU eaters on it. The experimental results demonstrate that our prototype successfully schedules the consolidated GPGPU apps on the basis of its scheduling policy and isolates resources among them.
Year
DOI
Venue
2017
10.1145/3127479.3132023
SoCC '17: ACM Symposium on Cloud Computing Santa Clara California September, 2017
Keywords
Field
DocType
GPGPU, Cloud Computing, Operating Systems
Graphics,Programming paradigm,Scheduling (computing),Computer science,Real-time computing,Schedule,Software,General-purpose computing on graphics processing units,Porting,Operating system,Cloud computing
Conference
ISBN
Citations 
PageRank 
978-1-4503-5028-0
2
0.38
References 
Authors
33
4
Name
Order
Citations
PageRank
Yusuke Suzuki1473.96
Hiroshi Yamada216925.23
Shinpei Kato395162.18
kenji kono41488.43