Computer Science, Machine Learning, and Applied Mathematics
TimeMonday, June 2616:30 - 18:30 CEST
DescriptionThe interaction of modern scientific applications in the exascale computing era with I/O resources is increasingly complex and important to application performance. Challenges in I/O performance are ubiquitous, from fault tolerance and resilience to coupled application workflows to heterogeneous and task-based systems. The purpose of this minisymposium is to facilitate a discussion of these challenges and recent novel research in high performance computing (HPC) addressing them. Topics discussed will include research in the areas of fault tolerance, heterogeneous data, and workflow or coupled applications, with an emphasis on computing resource, application, and data heterogeneity. We hope to enable a conversation about how these techniques can be used across various application use cases and thereby advance the state of the art in I/O performance. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.