The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Motivation for and Evaluation of the First Tensor Processing Unit
Abstract
The first-generation tensor processing unit (TPU) runs deep neural network (DNN) inference 15-30 times faster with 30-80 times better energy efficiency than contemporary CPUs and GPUs in similar semiconductor technologies. This domain-specific architecture (DSA) is a custom chip that has been deployed in Google datacenters since 2015, where it serves billions of people.
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Citations
Cites
In-Datacenter Performance Analysis of a Tensor Processing Unit
Jouppi, N. P., Young, C., Patil, N., Patterson, D., Agrawal, G., Bajwa, R., Bates, S., Bhatia, S., Boden, N., Borchers, A., et al. (2017) · Proceedings of the 44th Annual International Symposium on Computer Architecture · doi:10.1145/3079856.3080246 · Cited by 4,537
Self-citationWilliams, S., Waterman, A., & Patterson, D. A. (2009) · Communications of the ACM · doi:10.1145/1498765.1498785 · Cited by 2,798
Self-citation
Cited by
Valueva, M. V., Nagornov, N. N., Lyakhov, P. A., Valuev, G. V., & Chervyakov, N. I. (2020) · Mathematics and Computers in Simulation · doi:10.1016/j.matcom.2020.04.031 · Cited by 478
Deep learning in ultrasound imaging
van Sloun, R. J. G., Cohen, R., & Eldar, Y. C. (2020) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2932116 · Cited by 316
Sponge Examples: Energy-Latency Attacks on Neural Networks
Shumailov, I., Zhao, Y., Bates, D., Papernot, N., Mullins, R., & Anderson, R. (2021) · 2021 IEEE European Symposium on Security and Privacy (EuroS&P) · doi:10.1109/eurosp51992.2021.00024 · Cited by 125
A Cloud-Based Framework for Machine Learning Workloads and Applications
Lopez Garcia, A., De Lucas, J. M., Antonacci, M., Zu Castell, W., David, M., Hardt, M., Lloret Iglesias, L., Molto, G., Plociennik, M., Tran, V., et al. (2020) · IEEE Access · doi:10.1109/access.2020.2964386 · Cited by 108
Dong, P., Zhuang, J., Yang, Z., Ji, S., Li, Y., Xu, D., Huang, H., Hu, J., Jones, A. K., Shi, Y., et al. (2024) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2024.3443692 · Cited by 35
“In the cloud , to guarantee the quality of service, deep learning-based inference for the cloud services in Microsoft Bing Search [21], Microsoft Azure Cloud [22], [23], and Google Cloud [24], [25], [26], all have a single-digit millisecond latency budget to process.”
Metadata
- Authors
- Jouppi, N., Young, C., Patil, N., & Patterson, D.
- Venue
- IEEE Micro
- Published
- 2018-05
- Volume
- 38
- Issue
- 3
- Pages
- 10-19
- ISSN
- 0272-1732 (ISSN-L)
- 1937-4143
- OpenAlex
- W2801748224
- Cited by
- 239
- References
- 2
- FWCI
- 28.35
- Type
- journal article
- Language
- en
- Open access
- closed
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