Title
A dynamic CTA scheduling scheme for massive parallel computing.
Abstract
Recent computing devices execute massive parallel data requiring huge computing hardware. To satisfy increasing computing need, GPUs providing powerful computational capability are employed to execute both graphics and general-purpose applications (GPGPUs). In the GPGPU, executing multiple applications together can increase the data parallelism, resulting in high resource utilization. Improving the resource utilization of the GPGPU can increase the GPGPU performance. However, various kinds of applications have different execution time depending on their workload sizes. Therefore, if one application is completed earlier than the other ones, resource underutilization problem may happen because the hardware resource allocated for the early completed application becomes idle. In this work, a CTA-aware dynamic streaming multiprocessors scheduling scheme is proposed for multiple applications execution in the GPGPU to efficiently manage hardware resources. Simulation results show that the proposed CTA-aware dynamic SM scheduling scheme can increase the GPU performance by up to 25.6% on average.
Year
DOI
Venue
2017
10.1007/s10586-017-0768-9
Cluster Computing
Keywords
Field
DocType
GPGPU, Multiple applications, SM scheduling scheme, Resource utilization
Graphics,Idle,Workload,Scheduling (computing),Computer science,Parallel computing,Real-time computing,Data parallelism,General-purpose computing on graphics processing units,Execution time,Distributed computing
Journal
Volume
Issue
ISSN
20
1
1573-7543
Citations 
PageRank 
References 
1
0.35
10
Authors
5
Name
Order
Citations
PageRank
Dong Oh Son1214.19
cong thuan do241.77
Hong Jun Choi3305.74
Ji-Seung Nam4289.24
Cheol Hong Kim57324.39