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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Acknowledgment
This work is supported by the Standardization Research Project of Chinese Academy of Sciences No.BZ201800001.
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Luo, C. et al. (2019). AIoT Bench: Towards Comprehensive Benchmarking Mobile and Embedded Device Intelligence. In: Zheng, C., Zhan, J. (eds) Benchmarking, Measuring, and Optimizing. Bench 2018. Lecture Notes in Computer Science(), vol 11459. Springer, Cham. https://doi.org/10.1007/978-3-030-32813-9_4
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DOI: https://doi.org/10.1007/978-3-030-32813-9_4
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