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Abstract
This paper presents the case study of a non-intrusive porting of a monolithic C++ library for real-time 3D hand tracking, to the domain of edge-based computation. Towards a proof of concept, the case study considers a pair of workstations, a computationally powerful and a computationally weak one. By wrapping the C++ library in Java container and by capitalizing on a Java-based offloading infrastructure that supports both CPU and GPGPU computations, we are able to establish automatically the required server-client workflow that best addresses the resource allocation problem in the effort to execute from the weak workstation. As a result, the weak workstation can perform well at the task, despite lacking the sufficient hardware to do the required computations locally. This is achieved by offloading computations which rely on GPGPU, to the powerful workstation, across the network that connects them. We show the edge-based computation challenges associated with the information flow of the ported algorithm, demonstrate how we cope with them, and identify what needs to be improved for achieving even better performance.
Original language | English |
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Publisher | arXiv |
Number of pages | 6 |
Publication status | Published - 1 Apr 2018 |
Keywords
- Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Computer Vision and Pattern Recognition
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Dive into the research topics of 'On the Feasibility of Real-Time 3D Hand Tracking using Edge GPGPU Acceleration'. Together they form a unique fingerprint.Activities
- 1 Conference presentations
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Demo: Distributed Real-Time Generative 3D Hand Tracking using Edge GPGPU Acceleration
Sokol Kosta (Lecturer)
11 Jun 2018Activity: Talks and presentations › Conference presentations