Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Bill Jia"'
Autor:
Bill Jia, Arin Wongprommoon
Publikováno v:
BioTechniques, Vol 65, Iss 3, Pp 113-119 (2018)
[Graphic: see text] Synthetic biology has enormous potential to solve problems in health, agriculture, and energy. Bill Jia and Arin Wongprommoon explore engineering approaches to controlling biological processes.
Externí odkaz:
https://doaj.org/article/31496c36ddec47abbebeedd6f7848695
Autor:
Dheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Zhihao Jia, Andrew Tulloch, Srinivas Sridharan, Xing Liu, Mustafa Ozdal, Jade Nie, Jongsoo Park, Liang Luo, Jie (Amy) Yang, Leon Gao, Dmytro Ivchenko, Aarti Basant, Yuxi Hu, Jiyan Yang, Ehsan K. Ardestani, Xiaodong Wang, Rakesh Komuravelli, Ching-Hsiang Chu, Serhat Yilmaz, Huayu Li, Jiyuan Qian, Zhuobo Feng, Yinbin Ma, Junjie Yang, Ellie Wen, Hong Li, Lin Yang, Chonglin Sun, Whitney Zhao, Dimitry Melts, Krishna Dhulipala, KR Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Guoqiang Jerry Chen, Manoj Krishnan, Avinash Nayak, Krishnakumar Nair, Bharath Muthiah, Mahmoud khorashadi, Pallab Bhattacharya, Petr Lapukhov, Maxim Naumov, Ajit Mathews, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao
Deep learning recommendation models (DLRMs) are used across many business-critical services at Facebook and are the single largest AI application in terms of infrastructure demand in its data-centers. In this paper we discuss the SW/HW co-designed so
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b1a6d07c5739fe931da1f91ac4f756a
http://arxiv.org/abs/2104.05158
http://arxiv.org/abs/2104.05158
Autor:
Mikhail Smelyanskiy, Dheevatsa Mudigere, Xiaodong Wang, Udit Gupta, Carole-Jean Wu, Bradford Cottel, David Brooks, Xuan Zhang, Bill Jia, Brandon Reagen, Mark Hempstead, Maxim Naumov, Kim Hazelwood, Hsien-Hsin S. Lee, Liang Xiong, Andrey Malevich
Publikováno v:
HPCA
The widespread application of deep learning has changed the landscape of computation in data centers. In particular, personalized recommendation for content ranking is now largely accomplished using deep neural networks. However, despite their import
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::04af085a5721ef42f9a4798a26b03bcb
https://doi.org/10.1109/hpca47549.2020.00047
https://doi.org/10.1109/hpca47549.2020.00047
Autor:
David Brooks, Kevin Chen, Tommer Leyvand, Andrew Tulloch, Bill Jia, Yiming Wu, Sy Choudhury, Hao Lu, Kim Hazelwood, Yanghan Wang, Peizhao Zhang, Lin Qiao, Bram Wasti, Ran Xian, Peter Vajda, Brandon Reagen, Yangqing Jia, Fei Sun, Carole-Jean Wu, Yang Lu, Xiaodong Wang, Marat Dukhan, Eldad Isaac, Joe Spisak, Douglas Chen, Sungjoo Yoo
Publikováno v:
HPCA
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cca28b23ff7aff7afad048e5c2368cd
https://doi.org/10.1109/hpca.2019.00048
https://doi.org/10.1109/hpca.2019.00048
Autor:
Kim Hazelwood, Hsien-Hsin S. Lee, Bill Jia, Liu Ke, David Brooks, Martin Schatz, Maxim Naumov, Xuan Zhang, Benjamin Youngjae Cho, Carole-Jean Wu, Bert Maher, Amin Firoozshahian, Meng Li, Mark Hempstead, Utku Diril, Brandon Reagen, Mikhail Smelyanskiy, Vikas Chandra, Xiaodong Wang, Udit Gupta, Dheevatsa Mudigere
Publikováno v:
ISCA
Personalized recommendation systems leverage deep learning models and account for the majority of data center AI cycles. Their performance is dominated by memory-bound sparse embedding operations with unique irregular memory access patterns that pose
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::421f7b2188846753693aa1f8fa12cf0f
Autor:
Misha Smelyanskiy, Pieter Noordhuis, Bill Jia, Soumith Chintala, Jason Lu, Kim Hazelwood, Xiaodong Wang, Dmytro Dzhulgakov, Sarah Bird, Mohamed Fawzy, Aditya Kalro, Utku Diril, Liang Xiong, Kevin M. Lee, David Brooks, James Law, Yangqing Jia
Publikováno v:
HPCA
Machine learning sits at the core of many essential products and services at Facebook. This paper describes the hardware and software infrastructure that supports machine learning at global scale. Facebook's machine learning workloads are extremely d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a46a75c32a0ee1751730f8f9f878337b
https://doi.org/10.1109/hpca.2018.00059
https://doi.org/10.1109/hpca.2018.00059
Autor:
Richard Liu, Bill Jia, Rajesh Nishtala, John Liang, Jason Taylor, James Luo, Nick Hammer, Mark Drayton
Publikováno v:
CloudDP@EuroSys
In a social network, it is natural to have hot objects such as a celebrity's Facebook page. Duplicating hot object data in each cluster provides quick cache access and avoids stressing a single server's network or CPU resources. But duplicating cold
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f26b77ad8b30dffa2731267990783f8c
https://doi.org/10.1145/2460756.2460757
https://doi.org/10.1145/2460756.2460757
Autor:
Shunya Namiki, Hsien-Chih Huang, Julio Soares, Xihang Wu, Jeong Dong Kim, Bill Jiang, Vaanchit Srikumar, Xiuling Li
Publikováno v:
Advanced Photonics Research, Vol 2, Iss 3, Pp n/a-n/a (2021)
III–V semiconductor‐based photodiodes with graphene incorporated have been studied in recent years due to the attractive optoelectronic properties of graphene, including optical transparency and enhanced photoresponsivity. The photoresponsivity c
Externí odkaz:
https://doaj.org/article/e2a4415f5b354cd7b5d63e435b8e8972