tf-Darshan: Understanding Fine-grained I/O Performance in Machine Learning Workloads
- KTH Royal Institute of Technology
- Lawrence Livermore National Laboratory
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- AC52-07NA27344
- OSTI ID:
- 1830501
- Report Number(s):
- LLNL-CONF-810737; 1017340
- Country of Publication:
- United States
- Language:
- English
Similar Records
Characterizing Machine Learning I/O Workloads on Leadership Scale HPC Systems
Darshan I/O Runtime Monitoring .
Understanding and Leveraging the I/O Patterns of Emerging Machine Learning Analytics
Conference
·
Mon Nov 01 00:00:00 EDT 2021
·
OSTI ID:1885376
Darshan I/O Runtime Monitoring .
Conference
·
Tue Nov 01 00:00:00 EDT 2022
·
OSTI ID:2006147
Understanding and Leveraging the I/O Patterns of Emerging Machine Learning Analytics
Conference
·
Mon Feb 28 23:00:00 EST 2022
·
OSTI ID:1860590