|
|
The race to Exascale poses significant challenges for the collection and analysis of the vast amount of data that future HPC systems will produce, in terms of the increasing complexity of the machines, the scalability and intrusiveness of the adopted monitoring solution, and the interpretability and effective inference driven by the acquired data. The main scope of the 1st ISC-HPC International Workshop on Monitoring and Operational Data Analytics (MODA) is to provide insight into current trends in MODA, to identify potential gaps, and to offer an outlook into the future of the involved fields high performance-computing, databases, machine learning, and possible solutions for upcoming Exascale systems. Contributions matching the scope of the workshop will be related to:
This workshop is not targeting new solutions proposed in the context of application performance modeling and/or application performance analysis tools. Novel contributions in the area of compiler analysis, debugging, programming models and/or sustainability of scientific software are also considered out of the scope of the workshop.
MODA is becoming common practice at various international HPC sites. However, each site adopts a different, insular approach, rarely adopted in production environments and mostly limited to the visualisation of system and building infrastructure metrics for health check purposes. In this regard, we observe a gap between the collection of operational data and its meaningful and effective analysis and exploitation, which prevents the closing of the feedback loop between the monitored HPC system, its operation, and its end-users. Under these premises, the goals of the workshop can then be summarized in the following way:
Online user: 8 | Privacy |