News - ovis-hpc/ovis-wiki GitHub Wiki
NEWS from 2021 and beyond will be in the Discussions (announcement label) and no longer here
- 2020.12.27 - ovis-hpc transitioned to an organizational account for more flexible access control!
- 2020.12.27 - GitHub Discussions have been enabled
- 2020.08.04-06 - LDMSCON2020 - with tutorial videos and presentation links
- watch the repo for latest releases
Release News:
- V4 is now master!
- V4:
- 2019.11.12 - LDMS OVIS-4.3.3_Beta Release
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2019.10.22 - LDMS OVIS-4.3.2_Beta Release
- V4.3.X is incompatible with V4.2.X -- please recompile all code and utilities (e.g., ldms_ls).
- 2019.06.13 - LDMS OVIS-V4.2.3 Release
- 2019.02.28 - LDMS OVIS-V4.2.1-rc1 Release
- 2019.02.04 - LDMS OVIS-V4.2_Beta Release! This is deprecated as of OVIS-V4.2.1-rc1.
- V3:
- Latest Update: V3 branches continue to be hosted here, but will be deprecated soon.
- LDMS Demos and developers at SC! “Advances in HPC Monitoring, Run-Time Performance Analysis, Visualization, and Feedback” Wed Nov 22 @ DOE Booth 925 Station 2
- LDMS Users Group Meeting Conference in Orlando, Florida Oct 22-24.
- Interested in HPC Monitoring and Analysis? Workshop on Monitoring and Analysis for HPC Systems Plus Applications @ IEEE Cluster 2019 in Sept 2019!
- 2018.11 -- LDMS Demonstrations and Presentations at SC18:
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Platform Independent Run Time HPC Monitoring, Analysis, and Feedback at Any-Scale
J. Brandt -- Featured Presentation at DOE Booth Wed Nov 14 4-4:45 pm - System Monitoring Tools Demos at DOE Booth:
- Tue Nov 13: 11-12 and 3-4
- Wed Nov 14: 10-12
- BoF: Monitoring Large-Scale HPC Systems: Extracting and Presenting Meaningful System and Application Insights - Wed Nov 14 5:15-6:45
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Platform Independent Run Time HPC Monitoring, Analysis, and Feedback at Any-Scale
- 2018.11 -- New mailing list and user group telecons
- 2018.10 -- Documentation is being updated daily!
- 2017.05 -- LDMS v3 Tutorial Posted
- 2017 ISC High Performance 2017 (ISC) Gauss Award Winner: Diagnosing Performance Variations in HPC Applications Using Machine Learning - using LDMS monitoring data as the basis for Machine Learning-based Performance Diagnosis