Zobrazeno 1 - 10
of 1 912
pro vyhledávání: '"Jhunjhunwala, A."'
Erasure-coded computing has been successfully used in cloud systems to reduce tail latency caused by factors such as straggling servers and heterogeneous traffic variations. A majority of cloud computing traffic now consists of inference on neural ne
Externí odkaz:
http://arxiv.org/abs/2409.01420
Autor:
Parmar, Jupinder, Prabhumoye, Shrimai, Jennings, Joseph, Liu, Bo, Jhunjhunwala, Aastha, Wang, Zhilin, Patwary, Mostofa, Shoeybi, Mohammad, Catanzaro, Bryan
The impressive capabilities of recent language models can be largely attributed to the multi-trillion token pretraining datasets that they are trained on. However, model developers fail to disclose their construction methodology which has lead to a l
Externí odkaz:
http://arxiv.org/abs/2407.06380
Autor:
Nvidia, Adler, Bo, Agarwal, Niket, Aithal, Ashwath, Anh, Dong H., Bhattacharya, Pallab, Brundyn, Annika, Casper, Jared, Catanzaro, Bryan, Clay, Sharon, Cohen, Jonathan, Das, Sirshak, Dattagupta, Ayush, Delalleau, Olivier, Derczynski, Leon, Dong, Yi, Egert, Daniel, Evans, Ellie, Ficek, Aleksander, Fridman, Denys, Ghosh, Shaona, Ginsburg, Boris, Gitman, Igor, Grzegorzek, Tomasz, Hero, Robert, Huang, Jining, Jawa, Vibhu, Jennings, Joseph, Jhunjhunwala, Aastha, Kamalu, John, Khan, Sadaf, Kuchaiev, Oleksii, LeGresley, Patrick, Li, Hui, Liu, Jiwei, Liu, Zihan, Long, Eileen, Mahabaleshwarkar, Ameya Sunil, Majumdar, Somshubra, Maki, James, Martinez, Miguel, de Melo, Maer Rodrigues, Moshkov, Ivan, Narayanan, Deepak, Narenthiran, Sean, Navarro, Jesus, Nguyen, Phong, Nitski, Osvald, Noroozi, Vahid, Nutheti, Guruprasad, Parisien, Christopher, Parmar, Jupinder, Patwary, Mostofa, Pawelec, Krzysztof, Ping, Wei, Prabhumoye, Shrimai, Roy, Rajarshi, Saar, Trisha, Sabavat, Vasanth Rao Naik, Satheesh, Sanjeev, Scowcroft, Jane Polak, Sewall, Jason, Shamis, Pavel, Shen, Gerald, Shoeybi, Mohammad, Sizer, Dave, Smelyanskiy, Misha, Soares, Felipe, Sreedhar, Makesh Narsimhan, Su, Dan, Subramanian, Sandeep, Sun, Shengyang, Toshniwal, Shubham, Wang, Hao, Wang, Zhilin, You, Jiaxuan, Zeng, Jiaqi, Zhang, Jimmy, Zhang, Jing, Zhang, Vivienne, Zhang, Yian, Zhu, Chen
We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base, Nemotron-4-340B-Instruct, and Nemotron-4-340B-Reward. Our models are open access under the NVIDIA Open Model License Agreement, a permissive model license that allows distri
Externí odkaz:
http://arxiv.org/abs/2406.11704
Standard federated learning (FL) algorithms typically require multiple rounds of communication between the server and the clients, which has several drawbacks, including requiring constant network connectivity, repeated investment of computational re
Externí odkaz:
http://arxiv.org/abs/2403.12329
Autor:
Parmar, Jupinder, Prabhumoye, Shrimai, Jennings, Joseph, Patwary, Mostofa, Subramanian, Sandeep, Su, Dan, Zhu, Chen, Narayanan, Deepak, Jhunjhunwala, Aastha, Dattagupta, Ayush, Jawa, Vibhu, Liu, Jiwei, Mahabaleshwarkar, Ameya, Nitski, Osvald, Brundyn, Annika, Maki, James, Martinez, Miguel, You, Jiaxuan, Kamalu, John, LeGresley, Patrick, Fridman, Denys, Casper, Jared, Aithal, Ashwath, Kuchaiev, Oleksii, Shoeybi, Mohammad, Cohen, Jonathan, Catanzaro, Bryan
We introduce Nemotron-4 15B, a 15-billion-parameter large multilingual language model trained on 8 trillion text tokens. Nemotron-4 15B demonstrates strong performance when assessed on English, multilingual, and coding tasks: it outperforms all exist
Externí odkaz:
http://arxiv.org/abs/2402.16819
Autor:
Livne, Micha, Miftahutdinov, Zulfat, Tutubalina, Elena, Kuznetsov, Maksim, Polykovskiy, Daniil, Brundyn, Annika, Jhunjhunwala, Aastha, Costa, Anthony, Aliper, Alex, Aspuru-Guzik, Alán, Zhavoronkov, Alex
Publikováno v:
Chemical Science, 15(22), 8380-8389, 2024
Large Language Models (LLMs) have substantially driven scientific progress in various domains, and many papers have demonstrated their ability to tackle complex problems with creative solutions. Our paper introduces a new foundation model, nach0, cap
Externí odkaz:
http://arxiv.org/abs/2311.12410
Autor:
Mohammad Atif, Nitesh Tewari, Garima Jhunjhunwala, Hemlata Nehta, Morankar Rahul, Vijay Prakash Mathur, Kalpana Bansal
Publikováno v:
Journal of Indian Society of Pedodontics and Preventive Dentistry, Vol 42, Iss 3, Pp 249-254 (2024)
Background: Uncomplicated crown fractures of maxillary anterior teeth are common dental injuries, and the bonding of fractured fragments is recommended for management. Rehydration of fragments improves bonding and fracture resistance. Therefore, the
Externí odkaz:
https://doaj.org/article/1c91248d24bf46e583de3f0da06c8735
Exponential Tail Bounds on Queues: A Confluence of Non-Asymptotic Heavy Traffic and Large Deviations
In general, obtaining the exact steady-state distribution of queue lengths is not feasible. Therefore, we establish bounds for the tail probabilities of queue lengths. Specifically, we examine queueing systems under Heavy-Traffic (HT) conditions and
Externí odkaz:
http://arxiv.org/abs/2306.10187
Publikováno v:
Journal of Nanobiotechnology, Vol 22, Iss 1, Pp 1-11 (2024)
Abstract Background Ultrasound and photoacoustic (US/PA) imaging is a promising tool for in vivo visualization and assessment of drug delivery. However, the acoustic properties of the skull limit the practical application of US/PA imaging in the brai
Externí odkaz:
https://doaj.org/article/6edc9fda0fb048189ace905a12bdd0ac
Federated Averaging (FedAvg) remains the most popular algorithm for Federated Learning (FL) optimization due to its simple implementation, stateless nature, and privacy guarantees combined with secure aggregation. Recent work has sought to generalize
Externí odkaz:
http://arxiv.org/abs/2301.09604