GPU Enabled Serverless Computing Framework

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A new form of cloud computing, serverless computing, is drawing attention as a new way to design micro-services architectures. In a serverless computing environment, services are developed as service functional units. The function development environment of all serverless computing framework at present is CPU based. In this paper, we propose a GPU-supported serverless computing framework that can deploy services faster than existing serverless computing framework using CPU. Our core approach is to integrate the open source serverless computing framework with NVIDIA-Docker and deploy services based on the GPU support container. We have developed an API that connects the open source framework to the NVIDIA-Docker and commands that enable GPU programming. In our experiments, we measured the performance of the framework in various environments. As a result, developers who want to develop services through the framework can deploy high-performance micro services and developers who want to run deep learning programs without a GPU environment can run code on remote GPUs with little performance degradation.
Publisher
IEEE
Issue Date
2018-03
Language
English
Citation

26th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP), pp.533 - 540

ISSN
1066-6192
DOI
10.1109/PDP2018.2018.00090
URI
http://hdl.handle.net/10203/274750
Appears in Collection
CS-Conference Papers(학술회의논문)
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