CPU scheduling and memory management for interactive real-time applications

2011 ◽  
Vol 47 (5) ◽  
pp. 454-488 ◽  
Author(s):  
Shinpei Kato ◽  
Yutaka Ishikawa ◽  
Ragunathan Rajkumar
Keyword(s):  
Real Time ◽  
Memory Management ◽  
Cpu Scheduling ◽  
Real Time Applications

Maintaining Consistency Over A Network in Real-Time Applications

1989 ◽  
Author(s):  
Insup Lee ◽  
Susan Davidson ◽  
Victor Wolfe
Keyword(s):  
Real Time ◽  
Real Time Applications

Wave Forecasts in Muddy Coastal Environments: Model Development and Real-Time Applications

2004 ◽  
Author(s):  
Alexandru Sheremet ◽  
Gregory W. Stone ◽  
James M. Kaihatu
Keyword(s):  
Real Time ◽  
Model Development ◽  
Coastal Environments ◽  
Real Time Applications

Development of a Multi-Rate Simulation Model of an Unmanned Underwater Vehicle for Real-Time Applications

2009 ◽  
Vol 18 (3-4) ◽  
pp. 47-54 ◽  
Author(s):  
J.J. Zenor ◽  
D.J. Murray-Smith ◽  
E.W. McGookin ◽  
R.E. Crosbie
Keyword(s):  
Simulation Model ◽  
Real Time ◽  
Underwater Vehicle ◽  
Unmanned Underwater Vehicle ◽  
Real Time Applications

Peak-Power-Aware Energy Management for Periodic Real-Time Applications

2020 ◽  
Vol 39 (4) ◽  
pp. 779-788 ◽  
Author(s):  
Mohsen Ansari ◽  
Amir Yeganeh-Khaksar ◽  
Sepideh Safari ◽  
Alireza Ejlali
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Peak Power ◽  
Real Time Applications

scholarly journals Real-time FPGA-based implementation of the AKAZE algorithm with nonlinear scale space generation using image partitioning

2021 ◽  
Author(s):  
Parastoo Soleimani ◽  
David W. Capson ◽  
Kin Fun Li
Keyword(s):  
Real Time ◽  
Memory Management ◽  
Scale Space ◽  
Image Resolution ◽  
Hardware Architecture ◽  
Frame Rate ◽  
Time Sharing ◽  
Scale Invariant ◽  
Nonlinear Scale Space ◽  
Nonlinear Scale

AbstractThe first step in a scale invariant image matching system is scale space generation. Nonlinear scale space generation algorithms such as AKAZE, reduce noise and distortion in different scales while retaining the borders and key-points of the image. An FPGA-based hardware architecture for AKAZE nonlinear scale space generation is proposed to speed up this algorithm for real-time applications. The three contributions of this work are (1) mapping the two passes of the AKAZE algorithm onto a hardware architecture that realizes parallel processing of multiple sections, (2) multi-scale line buffers which can be used for different scales, and (3) a time-sharing mechanism in the memory management unit to process multiple sections of the image in parallel. We propose a time-sharing mechanism for memory management to prevent artifacts as a result of separating the process of image partitioning. We also use approximations in the algorithm to make hardware implementation more efficient while maintaining the repeatability of the detection. A frame rate of 304 frames per second for a $$1280 \times 768$$ 1280 × 768 image resolution is achieved which is favorably faster in comparison with other work.

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