Nipun Kwatra
Nipun Kwatra
Computer Science, Stanford University
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Cited by
Cited by
Texture optimization for example-based synthesis
V Kwatra, I Essa, A Bobick, N Kwatra
ACM Siggraph 2005 Papers, 795-802, 2005
Gandiva: Introspective cluster scheduling for deep learning
W Xiao, R Bhardwaj, R Ramjee, M Sivathanu, N Kwatra, Z Han, P Patel, ...
13th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2018
Two-way coupled SPH and particle level set fluid simulation
F Losasso, J Talton, N Kwatra, R Fedkiw
IEEE transactions on visualization and computer graphics 14 (4), 797-804, 2008
A method for avoiding the acoustic time step restriction in compressible flow
N Kwatra, J Su, JT Grétarsson, R Fedkiw
Journal of Computational Physics 228 (11), 4146-4161, 2009
Balancing efficiency and fairness in heterogeneous GPU clusters for deep learning
S Chaudhary, R Ramjee, M Sivathanu, N Kwatra, S Viswanatha
Proceedings of the Fifteenth European Conference on Computer Systems, 1-16, 2020
Texturing fluids
V Kwatra, D Adalsteinsson, T Kim, N Kwatra, M Carlson, M Lin
IEEE transactions on visualization and computer graphics 13 (5), 939-952, 2007
Varuna: scalable, low-cost training of massive deep learning models
S Athlur, N Saran, M Sivathanu, R Ramjee, N Kwatra
Proceedings of the Seventeenth European Conference on Computer Systems, 472-487, 2022
Respirenet: A deep neural network for accurately detecting abnormal lung sounds in limited data setting
S Gairola, F Tom, N Kwatra, M Jain
2021 43rd Annual International Conference of the IEEE Engineering in …, 2021
A framework for activity recognition and detection of unusual activities
D Mahajan, N Kwatra, S Jain, P Kalra, S Banerjee
Indian Conference on Computer Vision, Graphics and Image Processing 20, 2004
Numerically stable fluid–structure interactions between compressible flow and solid structures
JT Grétarsson, N Kwatra, R Fedkiw
Journal of Computational Physics 230 (8), 3062-3084, 2011
Fluid simulation with articulated bodies
N Kwatra, C Wojtan, M Carlson, IA Essa, PJ Mucha, G Turk
IEEE Transactions on Visualization and Computer Graphics 16 (1), 70-80, 2009
Sarathi: Efficient llm inference by piggybacking decodes with chunked prefills
A Agrawal, A Panwar, J Mohan, N Kwatra, BS Gulavani, R Ramjee
arXiv preprint arXiv:2308.16369, 2023
Unsupervised clustering using pseudo-semi-supervised learning
D Gupta, R Ramjee, N Kwatra, M Sivathanu
International Conference on Learning Representations, 2020
Practical Animation of Compressible Flow for ShockWaves and Related Phenomena.
N Kwatra, J Gretarsson, R Fedkiw
Symposium on Computer Animation, 207-215, 2010
Wide-minima density hypothesis and the explore-exploit learning rate schedule
N Iyer, V Thejas, N Kwatra, R Ramjee, M Sivathanu
Journal of Machine Learning Research 24 (65), 1-37, 2023
Singularity: Planet-scale, preemptive and elastic scheduling of AI workloads
D Shukla, M Sivathanu, S Viswanatha, B Gulavani, R Nehme, A Agrawal, ...
arXiv preprint arXiv:2202.07848, 2022
Taming throughput-latency tradeoff in llm inference with sarathi-serve
A Agrawal, N Kedia, A Panwar, J Mohan, N Kwatra, BS Gulavani, ...
arXiv preprint arXiv:2403.02310, 2024
SmartKC: smartphone-based corneal topographer for keratoconus detection
S Gairola, M Bohra, N Shaheer, N Jayaprakash, P Joshi, ...
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2021
Asynchronous evolution for fully‐implicit and semi‐implicit time integration
C Schroeder, N Kwatra, W Zheng, R Fedkiw
Computer Graphics Forum 30 (7), 1983-1992, 2011
Promoting content
V Raghunathan, DG Arthur, R Jain, EK Moxley, S Venkataraman, ...
US Patent 8,712,850, 2014
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