The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Workshop: PDSW23: 8th International Parallel Data Systems Workshop
Authors: Louis-Marie Nicolas (National Institute of Advanced Technologies of Brittany (ENSTA Bretagne), Bull Atos Technologies); Salim Mimouni and Philippe Couvée (Bull Atos Technologies); and Jalil Boukhobza (National Institute of Advanced Technologies of Brittany (ENSTA Bretagne))
Abstract: Modern HPC storage systems use tiers of heterogeneous storage technologies to compromise between capacity, performance, and cost. Prefetching is a technique used in these systems to move the right data at the right time from a slower to a high-performance tier in order to improve performance with a limited cost. Prefetching requires knowledge of the application I/O patterns, which can be extracted through I/O tracing tools or functions call stacks. State-of-the-art solutions based on the latter focus on applications with regular I/O profiles because of scalability issues. In this paper, we present an approach based on I/O call stacks that models I/O patterns for both regular and irregular applications by using directed graphs. We present two different models for prefetching with different trade-offs between complexity and accuracy of the prefetch predictions. Our models were able to predict I/Os with an accuracy of up to 98%, while keeping a lower overhead.
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