Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Parks Fields"'
Autor:
Nematollah Bidokhti, Caitie McCaffrey, Gary Grider, Andree Jacobson, Tim Emami, Deepthi Srinivasan, Riza O. Suminto, Peter Alvaro, Casey Golliher, Robert Ross, Biswaranjan Panda, Kevin Harms, Xing Lin, Robert Ricci, H. Birali Runesha, Russell Sears, Huaicheng Li, Haryadi S. Gunawi, Andrew D. Baptist, Kirk Webb, Weiguang Sheng, Mingzhe Hao, Swaminathan Sundararaman, Parks Fields
Publikováno v:
ACM Transactions on Storage. 14:1-26
Fail-slow hardware is an under-studied failure mode. We present a study of 114 reports of fail-slow hardware incidents, collected from large-scale cluster deployments in 14 institutions. We show that all hardware types such as disk, SSD, CPU, memory,
Autor:
Jim Brandt, Joe Greenseid, Steve Leak, Kaki Kelly, Jeremy Enos, Mark Klein, Nicholas Cardo, Dennis Hoppe, Parks Fields, Michael Gienger, James C. Williams, Ann C. Gentile, Kevin Pedretti, Stefan Andersson, Annette Greiner, Urpo Kaila, Richard A. Gerber, Alex Kristiansen, Yun He, Mike Showerman, Bilel Hadri, Cary Whitney, Mike Mason, Ville Ahlgren, Jason Repik, James H. Rogers, Susanna Salminen, Sudheer Chunduri, Jean-Guillaume Piccinali
Publikováno v:
CLUSTER
Monitoring of High Performance Computing (HPC) platforms is critical to successful operations, can provide insights into performance-impacting conditions, and can inform methodologies for improving science throughput. However, monitoring systems are
Publikováno v:
NAS
Erasure code storage systems are becoming popular choices for cloud storage systems due to cost-effective storage space saving schemes and higher fault-resilience capabilities. Both erasure code encoding and decoding procedures are involving heavy ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce2ce1425b05bbac6ada9d21864588de
https://zenodo.org/record/1277177
https://zenodo.org/record/1277177
Publikováno v:
IPDPS
In this paper we present a cost-effective, high bandwidth server I/O network architecture, named PaScal (Parallel and Scalable). We use the PaScal server I/O network to support data-intensive scientific applications running on very large-scale Linux