Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Glenn K. Lockwood"'
Publikováno v:
IEEE Access, Vol 11, Pp 3386-3401 (2023)
Burst Buffer is widely used in supercomputer centers to bridge the performance gap between computational power and the high-performance I/O systems. The primary role of Burst Buffer is to temporarily absorb the bursty I/O and reduce the heavy access
Externí odkaz:
https://doaj.org/article/f5b1ea64edb8453d997627d7424bfc2f
Autor:
Mihailo Isakov, Mikaela Currier, Eliakin del Rosario, Sandeep Madireddy, Prasanna Balaprakash, Philip Carns, Robert B. Ross, Glenn K. Lockwood, Michel A. Kinsy
I/O efficiency is crucial to productivity in scientific computing, but the increasing complexity of the system and the applications makes it difficult for practitioners to understand and optimize I/O behavior at scale. Data-driven machine learning-ba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::124d38a91a9303f0c7d5064b595c3dcc
http://arxiv.org/abs/2204.08180
http://arxiv.org/abs/2204.08180
Autor:
Katie Antypas, Eun-Kyu Byun, Jialin Liu, Donghun Koo, Soonwook Hwang, Jae-Hyuck Kwak, Kesheng Wu, Jaehwan Lee, Glenn K. Lockwood, Hyeonsang Eom
Publikováno v:
Journal of Parallel and Distributed Computing. 148:96-108
To meet the exascale I/O requirements for the High-Performance Computing (HPC), a new I/O subsystem, Burst Buffer, based on solid state drives (SSD), has been developed. However, the diverse HPC workloads and the bursty I/O pattern cause severe data
Publikováno v:
2021 IEEE/ACM Sixth International Parallel Data Systems Workshop (PDSW).
Autor:
Julian Kunkel, Jean-Thomas Acquaviva, Suren Byna, Adrian Jackson, Ivo Jimenez, Anthony Kougkas, Jay Lofstead, Glenn K. Lockwood, Carlos Maltzahn, George S. Markomanolis, Lingfang Zeng
This is the first issue of the journal of High-Performance Storage.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a63f5d5f0edda6b5cea9879f6b56dbf
Autor:
Brian Austin, Glenn K. Lockwood, Deborah Bard, Christopher S. Daley, Nicholas J. Wright, Lavanya Ramakrishnan, Devarshi Ghoshal
Publikováno v:
WORKS@SC
Scientific advances depend on the ability to effectively and efficiently use high performance computing (HPC) systems to manage and run large, complex scientific workflows. Towards understanding the characteristics of these large scientific workflows
Autor:
Christopher Daley, Lavanya Ramakrishnan, Sudip S. Dosanjh, Devarshi Ghoshal, Nicholas J. Wright, Glenn K. Lockwood
Scientific discoveries are increasingly dependent upon the analysis of large volumes of data from observations and simulations of complex phenomena. Scientists compose the complex analyses as workflows and execute them on large-scale HPC systems. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4dfe6e77909fcf27249986d4b8239b30
https://escholarship.org/uc/item/3t75f0qg
https://escholarship.org/uc/item/3t75f0qg
Autor:
Alex Sim, Hanul Sung, Hyung-Sin Kim, Glenn K. Lockwood, Chungyong Kim, Hyeonsang Eom, Jiwoo Bang
Publikováno v:
CCGRID
To avoid access to PFS, dedicated BB allocation is preferred despite of severe BB underutilization. Recently, new all-flash HPC storage systems with integrated BB and PFS are proposed, which speed up access to PFS. For this reason, we adopt BB over-s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::457e9ce0c5223249610509ae3160b6ed
https://escholarship.org/uc/item/2qp7f9pb
https://escholarship.org/uc/item/2qp7f9pb
Autor:
Shane Canon, Doug Jacobsen, Craig Tull, Dilworth Y. Parkinson, Peter Nugent, Eli Dart, Glenn K. Lockwood, Katie Antypas, L. Gerhardt, Inder Monga, Lavanya Ramakrishnan, Alexander Hexemer, Kjiersten Fagnan, Cory Snavely
Publikováno v:
Handbook on Big Data and Machine Learning in the Physical Sciences
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce51dd6ffd0204c89b21ec7aa2393a20
https://doi.org/10.1142/9789811204579_0017
https://doi.org/10.1142/9789811204579_0017
Publikováno v:
SC
Large-scale applications typically spend a large fraction of their execution time performing I/O to a parallel storage system. However, with rapid progress in compute and storage system stack of large-scale systems, it is critical to investigate and