Zobrazeno 1 - 10
of 258
pro vyhledávání: '"Bockelman, Brian"'
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:
Albin, Sam, Attebury, Garhan, Bloom, Kenneth, Bockelman, Brian, Lundstedt, Carl, Shadura, Oksana, Thiltges, John
The large data volumes expected from the High Luminosity LHC (HL-LHC) present challenges to existing paradigms and facilities for end-user data analysis. Modern cyberinfrastructure tools provide a diverse set of services that can be composed into a s
Externí odkaz:
http://arxiv.org/abs/2312.11485
The quest to understand the fundamental building blocks of nature and their interactions is one of the oldest and most ambitious of human scientific endeavors. CERN's Large Hadron Collider (LHC) represents a huge step forward in this quest. The disco
Externí odkaz:
http://arxiv.org/abs/2302.01317
Autor:
Flechas, Maria Acosta, Attebury, Garhan, Bloom, Kenneth, Bockelman, Brian, Gray, Lindsey, Holzman, Burt, Lundstedt, Carl, Shadura, Oksana, Smith, Nicholas, Thiltges, John
Prior to the public release of Kubernetes it was difficult to conduct joint development of elaborate analysis facilities due to the highly non-homogeneous nature of hardware and network topology across compute facilities. However, since the advent of
Externí odkaz:
http://arxiv.org/abs/2203.10161
Autor:
Benjamin, Doug, Bloom, Kenneth, Bockelman, Brian, Bryant, Lincoln, Cranmer, Kyle, Gardner, Rob, Hollowell, Chris, Holzman, Burt, Lançon, Eric, Rind, Ofer, Shadura, Oksana, Yang, Wei
The HL-LHC presents significant challenges for the HEP analysis community. The number of events in each analysis is expected to increase by an order of magnitude and new techniques are expected to be required; both challenges necessitate new services
Externí odkaz:
http://arxiv.org/abs/2203.08010
Autor:
Weitzel, Derek, McKee, Shawn, Bockelman, Brian Paul, Thiltges, John, Babik, Marian, Vukotic, Ilija
Modern network performance monitoring toolkits, such as perfSONAR, take a remarkable number of measurements about the local network environment. To gain a complete picture of network performance, however, one needs to aggregate data across a large nu
Externí odkaz:
http://arxiv.org/abs/2112.03074
Autor:
Fajardo, Edgar, Arora, Aashay, Davila, Diego, Gao, Richard, Würthwein, Frank, Bockelman, Brian
The High Luminosity Large Hadron Collider provides a data challenge. The amount of data recorded from the experiments and transported to hundreds of sites will see a thirty fold increase in annual data volume. A systematic approach to contrast the pe
Externí odkaz:
http://arxiv.org/abs/2103.12116
Autor:
Adamec, Matous, Attebury, Garhan, Bloom, Kenneth, Bockelman, Brian, Lundstedt, Carl, Shadura, Oksana, Thiltges, John
Data analysis in HEP has often relied on batch systems and event loops; users are given a non-interactive interface to computing resources and consider data event-by-event. The "Coffea-casa" prototype analysis facility is an effort to provide users w
Externí odkaz:
http://arxiv.org/abs/2103.01871
Autor:
Guan, Wen, Maeno, Tadashi, Bockelman, Brian Paul, Wenaus, Torre, Lin, Fahui, Padolski, Siarhei, Zhang, Rui, Alekseev, Aleksandr
The intelligent Data Delivery Service (iDDS) has been developed to cope with the huge increase of computing and storage resource usage in the coming LHC data taking. iDDS has been designed to intelligently orchestrate workflow and data management sys
Externí odkaz:
http://arxiv.org/abs/2103.00523
Autor:
Fajardo, Edgar, Wuerthwein, Frank, Bockelman, Brian, Livny, Miron, Thain, Greg, Clark, James Alexander, Couvares, Peter, Willis, Josh
During the first observation run the LIGO collaboration needed to offload some of its most, intense CPU workflows from its dedicated computing sites to opportunistic resources. Open Science Grid enabled LIGO to run PyCbC, RIFT and Bayeswave workflows
Externí odkaz:
http://arxiv.org/abs/2011.14995