Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Tailin Liang"'
Publikováno v:
ACM Transactions on Embedded Computing Systems. 22:1-27
Neural network processors and accelerators are domain-specific architectures deployed to solve the high computational requirements of deep learning algorithms. This article proposes a new instruction set extension for tensor computing, TCX, using Red
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ae240ff2b5c2a819e98525259c83506
https://doi.org/10.1145/3568310
https://doi.org/10.1145/3568310
Publikováno v:
2022 Design, Automation & Test in Europe Conference & Exhibition (DATE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::357c120738a542305a7da23e7a442a45
https://doi.org/10.23919/date54114.2022.9774626
https://doi.org/10.23919/date54114.2022.9774626
Deep neural networks have been applied in many applications exhibiting extraordinary abilities in the field of computer vision. However, complex network architectures challenge efficient real-time deployment and require significant computation resour
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5893273d8b62a79f42f732430739a03a
http://arxiv.org/abs/2101.09671
http://arxiv.org/abs/2101.09671
Publikováno v:
Pattern Recognition and Computer Vision ISBN: 9783030880125
PRCV (4)
PRCV (4)
High bandwidth requirements in edge devices can be a bottleneck for many systems - especially for accelerating both training and inference of deep neural networks. In this paper, we analyze feature map sparsity for several popular convolutional neura
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9200d4bdb8f696680dd12b3fac6edd40
https://doi.org/10.1007/978-3-030-88013-2_34
https://doi.org/10.1007/978-3-030-88013-2_34
Autor:
Chaoyang Tian, Tailin Liang, Shaobo Shi, Daniel Iancu, Chunxia Xu, Nianliang Yang, John Glossner, Xiaodong Zhang, Mayan Moudgill, Gary Nacer, Kerry Li, Huang Wei, Lei Wang
Publikováno v:
WCSP
We describe a programmable and scalable Convolutional Neural Network (CNN) hardware accelerator optimized for mobile and edge inference computing. The accelerator is comprised of 4 heterogeneous engines - input engine, filter engine, post processing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0bbcad1ac3f79e4907969e27cb977d14
https://doi.org/10.1109/wcsp49889.2020.9299736
https://doi.org/10.1109/wcsp49889.2020.9299736