Zobrazeno 1 - 10
of 3 408
pro vyhledávání: '"Venkatram, A."'
Autor:
Chitty-Venkata, Krishna Teja, Raskar, Siddhisanket, Kale, Bharat, Ferdaus, Farah, Tanikanti, Aditya, Raffenetti, Ken, Taylor, Valerie, Emani, Murali, Vishwanath, Venkatram
Large Language Models (LLMs) have propelled groundbreaking advancements across several domains and are commonly used for text generation applications. However, the computational demands of these complex models pose significant challenges, requiring e
Externí odkaz:
http://arxiv.org/abs/2411.00136
Autor:
Barwey, Shivam, Balin, Riccardo, Lusch, Bethany, Patel, Saumil, Balakrishnan, Ramesh, Pal, Pinaki, Maulik, Romit, Vishwanath, Venkatram
This work develops a distributed graph neural network (GNN) methodology for mesh-based modeling applications using a consistent neural message passing layer. As the name implies, the focus is on enabling scalable operations that satisfy physical cons
Externí odkaz:
http://arxiv.org/abs/2410.01657
Autor:
Barwey, Shivam, Pal, Pinaki, Patel, Saumil, Balin, Riccardo, Lusch, Bethany, Vishwanath, Venkatram, Maulik, Romit, Balakrishnan, Ramesh
A graph neural network (GNN) approach is introduced in this work which enables mesh-based three-dimensional super-resolution of fluid flows. In this framework, the GNN is designed to operate not on the full mesh-based field at once, but on localized
Externí odkaz:
http://arxiv.org/abs/2409.07769
Autor:
Hu, Muyan, Venkatram, Ashwin, Biswas, Shreyashri, Marimuthu, Balamurugan, Hou, Bohan, Oliaro, Gabriele, Wang, Haojie, Zheng, Liyan, Miao, Xupeng, Zhai, Jidong
Publikováno v:
Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems 3 (2024) 755-769
Kernel orchestration is the task of mapping the computation defined in different operators of a deep neural network (DNN) to the execution of GPU kernels on modern hardware platforms. Prior approaches optimize kernel orchestration by greedily applyin
Externí odkaz:
http://arxiv.org/abs/2406.09465
Autor:
A, Aniruth, Satpathy, Chirag, K, Jothika, M, Nitteesh, M, Gokulraj, K, Venkatram, G, Harshith, S, Shristi, Vani, Anushka, Spurgeon, Jonathan
Unmanned Aerial Vehicles (UAVs) have become pivotal in domains spanning military, agriculture, surveillance, and logistics, revolutionizing data collection and environmental interaction. With the advancement in drone technology, there is a compelling
Externí odkaz:
http://arxiv.org/abs/2401.02541
Autor:
Song, Shuaiwen Leon, Kruft, Bonnie, Zhang, Minjia, Li, Conglong, Chen, Shiyang, Zhang, Chengming, Tanaka, Masahiro, Wu, Xiaoxia, Rasley, Jeff, Awan, Ammar Ahmad, Holmes, Connor, Cai, Martin, Ghanem, Adam, Zhou, Zhongzhu, He, Yuxiong, Luferenko, Pete, Kumar, Divya, Weyn, Jonathan, Zhang, Ruixiong, Klocek, Sylwester, Vragov, Volodymyr, AlQuraishi, Mohammed, Ahdritz, Gustaf, Floristean, Christina, Negri, Cristina, Kotamarthi, Rao, Vishwanath, Venkatram, Ramanathan, Arvind, Foreman, Sam, Hippe, Kyle, Arcomano, Troy, Maulik, Romit, Zvyagin, Maxim, Brace, Alexander, Zhang, Bin, Bohorquez, Cindy Orozco, Clyde, Austin, Kale, Bharat, Perez-Rivera, Danilo, Ma, Heng, Mann, Carla M., Irvin, Michael, Pauloski, J. Gregory, Ward, Logan, Hayot, Valerie, Emani, Murali, Xie, Zhen, Lin, Diangen, Shukla, Maulik, Foster, Ian, Davis, James J., Papka, Michael E., Brettin, Thomas, Balaprakash, Prasanna, Tourassi, Gina, Gounley, John, Hanson, Heidi, Potok, Thomas E, Pasini, Massimiliano Lupo, Evans, Kate, Lu, Dan, Lunga, Dalton, Yin, Junqi, Dash, Sajal, Wang, Feiyi, Shankar, Mallikarjun, Lyngaas, Isaac, Wang, Xiao, Cong, Guojing, Zhang, Pei, Fan, Ming, Liu, Siyan, Hoisie, Adolfy, Yoo, Shinjae, Ren, Yihui, Tang, William, Felker, Kyle, Svyatkovskiy, Alexey, Liu, Hang, Aji, Ashwin, Dalton, Angela, Schulte, Michael, Schulz, Karl, Deng, Yuntian, Nie, Weili, Romero, Josh, Dallago, Christian, Vahdat, Arash, Xiao, Chaowei, Gibbs, Thomas, Anandkumar, Anima, Stevens, Rick
In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences. This could herald a new era of scientific exploration, bringing significant advancements across sectors fro
Externí odkaz:
http://arxiv.org/abs/2310.04610
Autor:
Emani, Murali, Foreman, Sam, Sastry, Varuni, Xie, Zhen, Raskar, Siddhisanket, Arnold, William, Thakur, Rajeev, Vishwanath, Venkatram, Papka, Michael E.
Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered as a promising approach to address some of the challenging problems becaus
Externí odkaz:
http://arxiv.org/abs/2310.04607
Publikováno v:
BMC Cancer, Vol 24, Iss 1, Pp 1-17 (2024)
Abstract Background Cancer cells alter their metabolic phenotypes with nutritional change. Single agent approaches targeting mitochondrial metabolism in cancer have failed due to either dose limiting off target toxicities, or lack of significant effi
Externí odkaz:
https://doaj.org/article/9ce6d929c5b04a88953aeb1211941401
Machine learning (ML) methods offer a wide range of configurable hyperparameters that have a significant influence on their performance. While accuracy is a commonly used performance objective, in many settings, it is not sufficient. Optimizing the M
Externí odkaz:
http://arxiv.org/abs/2309.14936
Autor:
Chitty-Venkata, Krishna Teja, Mittal, Sparsh, Emani, Murali, Vishwanath, Venkatram, Somani, Arun K.
Recent years have seen a phenomenal rise in performance and applications of transformer neural networks. The family of transformer networks, including Bidirectional Encoder Representations from Transformer (BERT), Generative Pretrained Transformer (G
Externí odkaz:
http://arxiv.org/abs/2307.07982