Pipelined Data-Parallel CPU/GPU Scheduling for Multi-DNN Real-Time Inference

2019 ◽  
Author(s):  
Yecheng Xiang ◽  
Hyoseung Kim
Keyword(s):  
Real Time ◽  
Data Parallel ◽  
Gpu Scheduling

A Data Parallel Implementation Scheme of Geometric Operations

2014 ◽  
Vol 519-520 ◽  
pp. 719-723
Author(s):  
Guang Wang
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Digital Image Processing ◽  
Digital Image ◽  
Parallel Implementation ◽  
Computation Complexity ◽  
The Real ◽  
Data Parallel ◽  
Implementation Scheme ◽  
Time Requirements

A data parallel implementation of geometric operations is proposed and conclusions are proved. It shows that the computation complexity of data parallel implementation scheme presented in this paper is Ο(M+N). It can be used to improve the efficiency of geometric operations and can easily meet the real time requirements of the digital image processing.

LaLaRAND: Flexible Layer-by-Layer CPU/GPU Scheduling for Real-Time DNN Tasks

2021 ◽  
Author(s):  
Woosung Kang ◽  
Kilho Lee ◽  
Jinkyu Lee ◽  
Insik Shin ◽  
Hoon Sung Chwa
Keyword(s):  
Real Time ◽  
Layer By Layer ◽  
Gpu Scheduling

Balancing Energy Efficiency and Real-Time Performance in GPU Scheduling

2021 ◽  
Author(s):  
Yidi Wang ◽  
Mohsen Karimi ◽  
Yecheng Xiang ◽  
Hyoseung Kim
Keyword(s):  
Energy Efficiency ◽  
Real Time ◽  
Time Performance ◽  
Balancing Energy ◽  
Gpu Scheduling

A Data-Parallel Approach for Real-Time MPEG-2 Video Encoding

1995 ◽  
Vol 30 (2) ◽  
pp. 129-146 ◽  
Author(s):  
S.M. Akramullah ◽  
I. Ahmad ◽  
M.L. Liou
Keyword(s):  
Real Time ◽  
Video Encoding ◽  
Data Parallel
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