First-Generation Inference Accelerator Deployment at Facebook

Autor: Anderson, Michael, Chen, Benny, Chen, Stephen, Deng, Summer, Fix, Jordan, Gschwind, Michael, Kalaiah, Aravind, Kim, Changkyu, Lee, Jaewon, Liang, Jason, Liu, Haixin, Lu, Yinghai, Montgomery, Jack, Moorthy, Arun, Nadathur, Satish, Naghshineh, Sam, Nayak, Avinash, Park, Jongsoo, Petersen, Chris, Schatz, Martin, Sundaram, Narayanan, Tang, Bangsheng, Tang, Peter, Yang, Amy, Yu, Jiecao, Yuen, Hector, Zhang, Ying, Anbudurai, Aravind, Balan, Vandana, Bojja, Harsha, Boyd, Joe, Breitbach, Matthew, Caldato, Claudio, Calvo, Anna, Catron, Garret, Chandwani, Sneh, Christeas, Panos, Cottel, Brad, Coutinho, Brian, Dalli, Arun, Dhanotia, Abhishek, Duncan, Oniel, Dzhabarov, Roman, Elmir, Simon, Fu, Chunli, Fu, Wenyin, Fulthorp, Michael, Gangidi, Adi, Gibson, Nick, Gordon, Sean, Hernandez, Beatriz Padilla, Ho, Daniel, Huang, Yu-Cheng, Johansson, Olof, Juluri, Shishir, Kanaujia, Shobhit, Kesarkar, Manali, Killinger, Jonathan, Kim, Ben, Kulkarni, Rohan, Lele, Meghan, Li, Huayu, Li, Huamin, Li, Yueming, Liu, Cynthia, Liu, Jerry, Maher, Bert, Mallipedi, Chandra, Mangla, Seema, Matam, Kiran Kumar, Mehta, Jubin, Mehta, Shobhit, Mitchell, Christopher, Muthiah, Bharath, Nagarkatte, Nitin, Narasimha, Ashwin, Nguyen, Bernard, Ortiz, Thiara, Padmanabha, Soumya, Pan, Deng, Poojary, Ashwin, Ye, Qi, Raginel, Olivier, Rajagopal, Dwarak, Rice, Tristan, Ross, Craig, Rotem, Nadav, Russ, Scott, Shah, Kushal, Shan, Baohua, Shen, Hao, Shetty, Pavan, Skandakumaran, Krish, Srinivasan, Kutta, Sumbaly, Roshan, Tauberg, Michael, Tzur, Mor, Verma, Sidharth, Wang, Hao, Wang, Man, Wei, Ben, Xia, Alex, Xu, Chenyu, Yang, Martin, Zhang, Kai, Zhang, Ruoxi, Zhao, Ming, Zhao, Whitney, Zhu, Rui, Mathews, Ajit, Qiao, Lin, Smelyanskiy, Misha, Jia, Bill, Rao, Vijay

In this paper, we provide a deep dive into the deployment of inference accelerators at Facebook. Many of our ML workloads have unique characteristics, such as sparse memory accesses, large model sizes, as well as high compute, memory and network band

Externí odkaz: http://arxiv.org/abs/2107.04140

Matrix-normal models for fMRI analysis

Autor: Shvartsman, Michael, Sundaram, Narayanan, Aoi, Mikio C., Charles, Adam, Wilke, Theodore C., Cohen, Jonathan D.

Multivariate analysis of fMRI data has benefited substantially from advances in machine learning. Most recently, a range of probabilistic latent variable models applied to fMRI data have been successful in a variety of tasks, including identifying si

Externí odkaz: http://arxiv.org/abs/1711.03058

Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data

Autor: Kurth, Thorsten, Zhang, Jian, Satish, Nadathur, Mitliagkas, Ioannis, Racah, Evan, Patwary, Mostofa Ali, Malas, Tareq, Sundaram, Narayanan, Bhimji, Wahid, Smorkalov, Mikhail, Deslippe, Jack, Shiryaev, Mikhail, Sridharan, Srinivas, Prabhat, Dubey, Pradeep

This paper presents the first, 15-PetaFLOP Deep Learning system for solving scientific pattern classification problems on contemporary HPC architectures. We develop supervised convolutional architectures for discriminating signals in high-energy phys

Externí odkaz: http://arxiv.org/abs/1708.05256

GraphMat: High performance graph analytics made productive

Autor: Sundaram, Narayanan, Satish, Nadathur Rajagopalan, Patwary, Md Mostofa Ali, Dulloor, Subramanya R, Vadlamudi, Satya Gautam, Das, Dipankar, Dubey, Pradeep

Given the growing importance of large-scale graph analytics, there is a need to improve the performance of graph analysis frameworks without compromising on productivity. GraphMat is our solution to bridge this gap between a user-friendly graph analy

Externí odkaz: http://arxiv.org/abs/1503.07241

Understanding data storage and ingestion for large-scale deep recommendation model training

Autor: Mark Zhao, Niket Agarwal, Aarti Basant, Buğra Gedik, Satadru Pan, Mustafa Ozdal, Rakesh Komuravelli, Jerry Pan, Tianshu Bao, Haowei Lu, Sundaram Narayanan, Jack Langman, Kevin Wilfong, Harsha Rastogi, Carole-Jean Wu, Christos Kozyrakis, Parik Pol

Publikováno v: Proceedings of the 49th Annual International Symposium on Computer Architecture.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cad44daa1e8b7357b692548a25592146
https://doi.org/10.1145/3470496.3533044