Bridging Storage Semantics using Data Labels and Asynchronous I/O
Authors: A. Kougkas, H. Devarajan, X.-H. Sun
Date: November, 2020
Venue: ACM Transactions on Storage (TOS'20), Vol 16, No 4, Article 22, Nov. 2020
Type: Journal
Abstract
In the era of data-intensive computing, large-scale applications, in both scientific and the BigData communities, demonstrate unique I/O requirements leading to a proliferation of different storage devices and software stacks, many of which have conflicting requirements. Further, new hardware technologies and system designs create a hierarchical composition that may be ideal for computational storage operations. In this paper, we investigate how to support a wide variety of conflicting I/O workloads under a single storage system. We introduce the idea of a Label, a new data representation, and, we present LABIOS: a new, distributed, Label- based I/O system. LABIOS boosts I/O performance by up to 17x via asynchronous I/O, supports heterogeneous storage resources, offers storage elasticity, and promotes in-situ analytics and software defined storage support via data provisioning. LABIOS demonstrates the effectiveness of storage bridging to support the convergence of HPC and BigData workloads on a single platform.
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DOI: 10.1145/3415579