Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Kiran Pamnany"'
Autor:
Zhaoyi Shen, Lucas C. Wilcox, Thomas H. Gibson, Yassine Tissaoui, Maciej Waruszewski, Tapio Schneider, Francis X. Giraldo, Kiran Pamnany, Simone Marras, Jeremy E. Kozdon, Akshay Sridhar, Valentin Churavy, Simon Byrne, Charles Kawczynski
We introduce ClimateMachine, a new open-source atmosphere modeling framework which uses the Julia language and is designed to be scalable on central processing units (CPUs) and graphics processing units (GPUs). ClimateMachine uses a common framework
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::30cc278585c2a885f80ac3e2d5e7d7d0
https://doi.org/10.5194/gmd-2021-335
https://doi.org/10.5194/gmd-2021-335
Autor:
Prabhat, Ryan Giordano, David J. Schlegel, Keno Fischer, Jon McAuliffe, Kiran Pamnany, Jeffrey Regier, Andreas Noack, Maximilian Lam, R. C. Thomas, Steve Howard, Jarrett Revels
Publikováno v:
Journal of Parallel and Distributed Computing. 127:89-104
A key task in astronomy is to locate astronomical objects in images and to characterize them according to physical parameters such as brightness, color, and morphology. This task, known as cataloging, is challenging for several reasons: many astronom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5dc7563bcad22d866abc86161b0e9b3
https://doi.org/10.1016/j.jpdc.2018.12.008
https://doi.org/10.1016/j.jpdc.2018.12.008
Publikováno v:
JuliaCon Proceedings. 1:54
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8e1752cd8a1e3526bf13d91e9323651
https://doi.org/10.21105/jcon.00054
https://doi.org/10.21105/jcon.00054
Autor:
David J. Schlegel, Steve Howard, Jarrett Revels, Prabhat, Maximilian Lam, Kiran Pamnany, R. C. Thomas, Andreas Noack, Ryan Giordano, Jeffrey Regier, Keno Fischer, Jon McAuliffe
Publikováno v:
IPDPS
Astronomical catalogs derived from wide-field imaging surveys are an important tool for understanding the Universe. We construct an astronomical catalog from 55 TB of imaging data using Celeste, a Bayesian variational inference code written entirely
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1c9cded7ea02730744194dcccb47862
http://arxiv.org/abs/1801.10277
http://arxiv.org/abs/1801.10277
Autor:
Dhiraj D. Kalamkar, Karthikeyan Vaidyanathan, Kiran Pamnany, Jeff R. Hammond, Dipankar Das, Pavan Balaji, Jongsoo Park, Bálint Joó
Publikováno v:
SC
We present a new approach for multithreaded communication and asynchronous progress in MPI applications, wherein we offload communication processing to a dedicated thread. The central premise is that given the rapidly increasing core counts on modern
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::69ecd48db3e576220f2aad3d67fc6279
https://doi.org/10.1145/2807591.2807602
https://doi.org/10.1145/2807591.2807602
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319201184
Irregular applications are challenging to scale on supercomputers due to the difficulty of balancing load across large numbers of nodes. This challenge is exacerbated by the increasing heterogeneity of modern supercomputers in which nodes often conta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96228a59ee6382074c4e41dd72183196
https://doi.org/10.1007/978-3-319-20119-1_10
https://doi.org/10.1007/978-3-319-20119-1_10
Autor:
Yong Dong, Maneesha Aluru, Srinivas Aluru, Kiran Pamnany, Min Xie, Sriram P. Chockalingam, Sanchit Misra, Md. Vasimuddin
Publikováno v:
SC
Learning Bayesian networks is NP-hard. Even with recent progress in heuristic and parallel algorithms, modeling capabilities still fall short of the scale of the problems encountered. In this paper, we present a massively parallel method for Bayesian
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d833449761d0eac45d8e2a7f1c859c64
https://doi.org/10.1109/sc.2014.43
https://doi.org/10.1109/sc.2014.43
Autor:
Kiran Pamnany, Alexander Heinecke, Daehyun Kim, Dhiraj D. Kalamkar, Mikhail Smelyanskiy, Jongsoo Park, Bálint Joó, Bharat Kaul, Karthikeyan Vaidyanathan, Aniruddha G. Shet, Pradeep Dubey
Publikováno v:
IPDPS
Intel Xeon Phi coprocessor-based clusters offer high compute and memory performance for parallel workloads and also support direct network access. Many real world applications are significantly impacted by network characteristics and to maximize the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f42d4517d65ad1c2562c1c76ea4920f
https://doi.org/10.1109/ipdps.2014.113
https://doi.org/10.1109/ipdps.2014.113
Publikováno v:
IPDPS
Construction of whole-genome networks from large-scale gene expression data is an important problem in systems biology. While several techniques have been developed, most cannot handle network reconstruction at the whole-genome scale, and the few tha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d9b50f4ee60b0afbecbd6378c5d31846
https://doi.org/10.1109/ipdps.2014.35
https://doi.org/10.1109/ipdps.2014.35
Autor:
Mikhail Smelyanskiy, Karthikeyan Vaidyanathan, Pradeep Dubey, Victor W. Lee, Bálint Joó, Dhiraj D. Kalamkar, Kiran Pamnany, William A. Watson
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783642387494
ISC
ISC
Lattice Quantum Chromodynamics (LQCD) is currently the only known model independent, non perturbative computational method for calculations in the theory of the strong interactions, and is of importance in studies of nuclear and high energy physics.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94d81919cb0873b575a2f414957397a1
https://doi.org/10.1007/978-3-642-38750-0_4
https://doi.org/10.1007/978-3-642-38750-0_4