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2019 | OriginalPaper | Chapter

AIoT Bench: Towards Comprehensive Benchmarking Mobile and Embedded Device Intelligence

Authors : Chunjie Luo, Fan Zhang, Cheng Huang, Xingwang Xiong, Jianan Chen, Lei Wang, Wanling Gao, Hainan Ye, Tong Wu, Runsong Zhou, Jianfeng Zhan

Published in: Benchmarking, Measuring, and Optimizing

Publisher: Springer International Publishing

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Abstract

Due to increasing amounts of data and compute resources, the deep learning achieves many successes in various domains. Recently, researchers and engineers make effort to apply the intelligent algorithms to the mobile or embedded devices. In this paper, we propose a benchmark suite, AIoT Bench, to evaluate the AI ability of mobile and embedded devices. Our benchmark (1) covers different application domains, e.g. image recognition, speech recognition and natural language processing; (2) covers different platforms, including Android and Raspberry Pi; (3) covers different development frameworks, including TensorFlow and Caffe2; (4) offers both end-to-end application workloads and micro workloads.

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previous chapter Edge AIBench: Towards Comprehensive End-to-End Edge Computing Benchmarking

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Title: AIoT Bench: Towards Comprehensive Benchmarking Mobile and Embedded Device Intelligence
Authors: Chunjie Luo
Fan Zhang
Cheng Huang
Xingwang Xiong
Jianan Chen
Lei Wang
Wanling Gao
Hainan Ye
Tong Wu
Runsong Zhou
Jianfeng Zhan
Publisher: Springer International Publishing
Book: Benchmarking, Measuring, and Optimizing
Print ISBN: 978-3-030-32812-2

Electronic ISBN: 978-3-030-32813-9

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-32813-9_4

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