EDLAB : a benchmark for edge deep learning accelerators
A new trend tends to deploy deep learning algorithms to edge environments to mitigate privacy and latency issues from cloud computing. Diverse edge deep learning accelerators are devised to speed up the inference of deep learning algorithms on edge devices. Various edge deep learning accelerator...
Saved in:
Main Authors: | Kong, Hao, Huai, Shuo, Liu, Di, Zhang, Lei, Chen, Hui, Zhu, Shien, Li, Shiqing, Liu, Weichen, Rastogi, Manu, Subramaniam, Ravi, Athreya, Madhu, Lewis, M. Anthony |
---|---|
其他作者: | School of Computer Science and Engineering |
格式: | Article |
語言: | English |
出版: |
2022
|
主題: | |
在線閱讀: | https://hdl.handle.net/10356/155807 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
機構: | Nanyang Technological University |
語言: | English |
相似書籍
-
Resource characterisation of personal-scale sensing models on edge accelerators
由: ANTONINI, Mattia, et al.
出版: (2019) -
Dynamic benchmarking methodology for quality function deployment
由: Raharjo, H., et al.
出版: (2014) -
Collate: collaborative neural network learning for latency-critical edge systems
由: Huai, Shuo, et al.
出版: (2023) -
Latency-constrained DNN architecture learning for edge systems using zerorized batch normalization
由: Huai, Shuo, et al.
出版: (2023) -
Rapid prototyping and manufacturing benchmarking
由: MANI MAHESH
出版: (2010)