On the role of burst buffers in leadership-class storage systems

TLDR

High‑performance computing systems are pushing parallel file systems to their bandwidth and client limits, prompting exploration of new storage designs. This study simulates and evaluates a burst‑buffer tiered storage architecture for large‑scale HPC workloads. By analyzing real I/O traces, extending the CODES simulator with a burst‑buffer model, an I/O kernel language, and a suite of derived kernels, the authors benchmarked multi‑application workloads across various burst‑buffer configurations. The results show that burst buffers increase application‑perceived throughput and lower the external storage bandwidth required to achieve a target throughput.

Abstract

The largest-scale high-performance (HPC) systems are stretching parallel file systems to their limits in terms of aggregate bandwidth and numbers of clients. To further sustain the scalability of these file systems, researchers and HPC storage architects are exploring various storage system designs. One proposed storage system design integrates a tier of solid-state burst buffers into the storage system to absorb application I/O requests. In this paper, we simulate and explore this storage system design for use by large-scale HPC systems. First, we examine application I/O patterns on an existing large-scale HPC system to identify common burst patterns. Next, we describe enhancements to the CODES storage system simulator to enable our burst buffer simulations. These enhancements include the integration of a burst buffer model into the I/O forwarding layer of the simulator, the development of an I/O kernel description language and interpreter, the development of a suite of I/O kernels that are derived from observed I/O patterns, and fidelity improvements to the CODES models. We evaluate the I/O performance for a set of multiapplication I/O workloads and burst buffer configurations. We show that burst buffers can accelerate the application perceived throughput to the external storage system and can reduce the amount of external storage bandwidth required to meet a desired application perceived throughput goal.