BCEdge: SLO-Aware DNN Inference Services With Adaptive Batch-Concurrent Scheduling on Edge Devices
Author:
Affiliation:
1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, China
2. International Research Institute for Artificial Intelligence, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong, China
Funder
National Key Research and Development Program of China
An Open Competition Project of Heilongjiang Province, China, on Research and Application of Key Technologies for Intelligent Farming Decision Platform
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/4275028/10643497/10549973.pdf?arnumber=10549973
Reference57 articles.
1. Clipper: A low-latency online prediction serving system;Crankshaw
2. BATCH: Machine Learning Inference Serving on Serverless Platforms with Adaptive Batching
3. Serving heterogeneous machine learning models on multi-GPU servers with spatio-temporal sharing;Choi
4. Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding;Han;arXiv:1510.00149,2015
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