I/O performance analysis of machine learning workloads on leadership scale supercomputer

Author:

Karimi Ahmad MaroofORCID,Paul Arnab K.,Wang Feiyi

Funder

Office of Science

U.S. Department of Energy

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Modeling and Simulation,Software

Reference28 articles.

1. Reliability-aware approach: An incremental checkpoint/restart model in HPC environments;Naksinehaboon,2008

2. I/O characterization of big data workloads in data centers;Pan,2014

3. Understanding and improving computational science storage access through continuous characterization;Carns;ACM Trans. Storage (TOS),2011

4. B.K. Pasquale, G.C. Polyzos, Dynamic I/O Characterization of I/O Intensive Scientific Applications, in: ACM/IEEE Conference on Supercomputing, 1994, pp. 660–669.

5. I/O characterization on a parallel file system;Narayan,2010

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