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Characterizing Storage Workloads with Counter Stacks

Thursday, August 7, 2014 - 2:15pm
Authors: 

Jake Wires, Stephen Ingram, Zachary Drudi, Nicholas J. A. Harvey, and Andrew Warfield, Coho Data

Abstract: 

Existing techniques for identifying working set sizes based on miss ratio curves (MRCs) have large memory overheads which make them impractical for storage workloads. We present a novel data structure, the counter stack, which can produce approximate MRCs while using sublinear space. We show how counter stacks can be checkpointed to produce workload representations that are many orders of magnitude smaller than full traces, and we describe techniques for estimating MRCs of arbitrary workload combinations over arbitrary windows in time. Finally, we show how online analysis using counter stacks can provide valuable insight into live workloads.

Jake Wires, Coho Data

Stephen Ingram, Coho Data

Zachary Drudi, Coho Data

Nicholas J. A. Harvey, Coho Data

Andrew Warfield, Coho Data

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BibTeX
@inproceedings {186181,
author = {Jake Wires and Stephen Ingram and Zachary Drudi and Nicholas J. A. Harvey and Andrew Warfield},
title = {Characterizing Storage Workloads with Counter Stacks},
booktitle = {11th USENIX Symposium on Operating Systems Design and Implementation (OSDI 14)},
year = {2014},
isbn = { 978-1-931971-16-4},
address = {Broomfield, CO},
pages = {335--349},
url = {https://www.usenix.org/conference/osdi14/technical-sessions/presentation/wires},
publisher = {USENIX Association},
month = oct,
}
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