Zobrazeno 1 - 10
of 229
pro vyhledávání: '"Guiang Jonathan"'
Publikováno v:
EPJ Web of Conferences, Vol 295, p 01001 (2024)
Due to the increased demand of network traffic expected during the HL-LHC era, the T2 sites in the USA will be required to have 400Gbps of available bandwidth to their storage solution. With the above in mind we are pursuing a scale test of XRootD so
Externí odkaz:
https://doaj.org/article/9e9e3a5b0f4c40b386385b516b1ee30f
Autor:
Balcas Justas, Newman Harvey, Bhat Preeti P., Würthwein Frank, Guiang Jonathan, Arora Aashay, Davila Diego, Graham John, Hutton Thomas, Lehman Tom, Yang Xi, Guok Chin, Alexander Mason David, Gutsche Oliver, DeMar Phil, Huang Chih-Hao, Asif Shah Syed, Litvintsev Dmitry, Heath Ryan, Malone Melo Andrew
Publikováno v:
EPJ Web of Conferences, Vol 295, p 01009 (2024)
The Large Hadron Collider (LHC) experiments distribute data by leveraging a diverse array of National Research and Education Networks (NRENs), where experiment data management systems treat networks as a “blackbox” resource. After the High Lumino
Externí odkaz:
https://doaj.org/article/4cfa57710d9e4731ae0fafd6d3a9ddd2
Autor:
Andrijauskas Fabio, Sfiligoi Igor, Davila Diego, Arora Aashay, Guiang Jonathan, Bockelman Brian, Thain Greg, Würthwein Frank
Publikováno v:
EPJ Web of Conferences, Vol 295, p 07046 (2024)
Creating new materials, discovering new drugs, and simulating systems are essential processes for research and innovation and require substantial computational power. While many applications can be split into many smaller independent tasks, some cann
Externí odkaz:
https://doaj.org/article/99eaf4d1d7cf48118c775b4e54b3c278
Autor:
Vourliotis, Emmanouil, Chang, Philip, Elmer, Peter, Gu, Yanxi, Guiang, Jonathan, Krutelyov, Vyacheslav, Narayanan, Balaji Venkat Sathia, Niendorf, Gavin, Reid, Michael, Silva, Mayra, Tascon, Andres Rios, Tadel, Matevž, Wittich, Peter, Yagil, Avraham
Charged particle reconstruction is one the most computationally heavy components of the full event reconstruction of Large Hadron Collider (LHC) experiments. Looking to the future, projections for the High Luminosity LHC (HL-LHC) indicate a superline
Externí odkaz:
http://arxiv.org/abs/2407.18231
Autor:
Guiang, Jonathan, Krutelyov, Slava, Vourliotis, Manos, Gu, Yanxi, Yagil, Avi, Narayanan, Balaji Venkat Sathia, Tadel, Matevz, Chang, Philip, Silva, Mayra, Niendorf, Gavin, Wittich, Peter, Reid, Tres, Elmer, Peter
In this work, we present a study on ways that tracking algorithms can be improved with machine learning (ML). We base this study on the line segment tracking (LST) algorithm that we have designed to be naturally parallelized and vectorized in order t
Externí odkaz:
http://arxiv.org/abs/2403.13166
Autor:
Andrijauskas, Fabio, Sfiligoi, Igor, Davila, Diego, Arora, Aashay, Guiang, Jonathan, Bockelman, Brian, Thain, Greg, Wurthwein, Frank
Creating new materials, discovering new drugs, and simulating systems are essential processes for research and innovation and require substantial computational power. While many applications can be split into many smaller independent tasks, some cann
Externí odkaz:
http://arxiv.org/abs/2402.05244
Autor:
Arora, Aashay, Guiang, Jonathan, Davila, Diego, Würthwein, Frank, Balcas, Justas, Newman, Harvey
Due to the increased demand of network traffic expected during the HL-LHC era, the T2 sites in the USA will be required to have 400Gbps of available bandwidth to their storage solution. With the above in mind we are pursuing a scale test of XRootD so
Externí odkaz:
http://arxiv.org/abs/2312.12589
Autor:
Fajardo Edgar, Tadel Matevz, Balcas Justas, Tadel Alja, Würthwein Frank, Davila Diego, Guiang Jonathan, Sfiligoi Igor
Publikováno v:
EPJ Web of Conferences, Vol 245, p 04042 (2020)
The University of California system maintains excellent networking between its campuses and a number of other Universities in California, including Caltech, most of them being connected at 100 Gbps. UCSD and Caltech Tier2 centers have joined their di
Externí odkaz:
https://doaj.org/article/b2926a3eab7a4c4b9c0c87cf46f044bd
Autor:
Agarwal, Manan, Alameda, Jay, Audenaert, Jeroen, Benoit, Will, Beveridge, Damon, Bhattacharya, Meghna, Chatterjee, Chayan, Chatterjee, Deep, Chen, Andy, Cholayil, Muhammed Saleem, Chou, Chia-Jui, Choudhary, Sunil, Coughlin, Michael, Dax, Maximilian, Desai, Aman, Di Luca, Andrea, Duarte, Javier Mauricio, Farrell, Steven, Feng, Yongbin, Goodarzi, Pooyan, Govorkova, Ekaterina, Graham, Matthew, Guiang, Jonathan, Gunny, Alec, Guo, Weichangfeng, Hakenmueller, Janina, Hawks, Ben, Hsu, Shih-Chieh, Jawahar, Pratik, Ju, Xiangyang, Katsavounidis, Erik, Kellis, Manolis, Khoda, Elham E, Lahbabi, Fatima Zahra, Lian, Van Tha Bik, Liu, Mia, Malanchev, Konstantin, Marx, Ethan, McCormack, William Patrick, McLeod, Alistair, Mo, Geoffrey, Moreno, Eric Anton, Muthukrishna, Daniel, Narayan, Gautham, Naylor, Andrew, Neubauer, Mark, Norman, Michael, Omer, Rafia, Pedro, Kevin, Peterson, Joshua, Pürrer, Michael, Raikman, Ryan, Raj, Shivam, Ricker, George, Robbins, Jared, Samani, Batool Safarzadeh, Scholberg, Kate, Schuy, Alex, Skliris, Vasileios, Soni, Siddharth, Sravan, Niharika, Sutton, Patrick, Villar, Victoria Ashley, Wang, Xiwei, Wen, Linqing, Wuerthwein, Frank, Yang, Tingjun, Yeh, Shu-Wei
Modern large-scale physics experiments create datasets with sizes and streaming rates that can exceed those from industry leaders such as Google Cloud and Netflix. Fully processing these datasets requires both sufficient compute power and efficient w
Externí odkaz:
http://arxiv.org/abs/2306.08106
Autor:
Würthwein, Frank, Guiang, Jonathan, Arora, Aashay, Davila, Diego, Graham, John, Mishin, Dima, Hutton, Thomas, Sfiligoi, Igor, Newman, Harvey, Balcas, Justas, Lehman, Tom, Yang, Xi, Guok, Chin
Unique scientific instruments designed and operated by large global collaborations are expected to produce Exabyte-scale data volumes per year by 2030. These collaborations depend on globally distributed storage and compute to turn raw data into scie
Externí odkaz:
http://arxiv.org/abs/2209.13714