Affiliation:
1. UC Santa Cruz Santa Cruz, California, USA
Abstract
Modern, large-scale scientific computing runs on complex exascale storage systems that support even more complex data workloads. Understanding the data access and movement patterns is vital for informing the design of future iterations of existing systems and next-generation systems. Yet we are lacking in publicly available traces and tools to help us understand even one system in depth, let alone correlate long-term cross-system trends.
Publisher
Association for Computing Machinery (ACM)
Subject
Genetics,Animal Science and Zoology