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Home » Automatic Identification of Application I/O Signatures from Noisy Server-Side Traces
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Automatic Identification of Application I/O Signatures from Noisy Server-Side Traces

Authors: 

Yang Liu, North Carolina State University; Raghul Gunasekaran, Oak Ridge National Laboratory; Xiaosong Ma, Qatar Computing Research Institute and North Carolina State University; Sudharshan S. Vazhkudai, Oak Ridge National Laboratory

Abstract: 

Competing workloads on a shared storage system cause I/O resource contention and application performance vagaries. This problem is already evident in today’s HPC storage systems and is likely to become acute at exascale. We need more interaction between application I/O requirements and system software tools to help alleviate the I/O bottleneck, moving towards I/O-aware job scheduling. However, this requires rich techniques to capture application I/O characteristics, which remain evasive in production systems.

Traditionally, I/O characteristics have been obtained using client-side tracing tools, with drawbacks such as non-trivial instrumentation/development costs, large trace traffic, and inconsistent adoption. We present a novel approach, I/O Signature Identifier (IOSI), to characterize the I/O behavior of data-intensive applications. IOSI extracts signatures from noisy, zero-overhead server-side I/O throughput logs that are already collected on today’s supercomputers, without interfering with the compiling/execution of applications. We evaluated IOSI using the Spider storage system at Oak Ridge National Laboratory, the S3D turbulence application (running on 18,000 Titan nodes), and benchmark-based pseudo-applications. Through our experiments we confirmed that IOSI effectively extracts an application’s I/O signature despite significant server-side noise. Compared to client-side tracing tools, IOSI is transparent, interface-agnostic, and incurs no overhead. Compared to alternative data alignment techniques (e.g., dynamic time warping), it offers higher signature accuracy and shorter processing time.

Yang Liu, North Carolina State University

Raghul Gunasekaran, Oak Ridge National Laboratory

Xiaosong Ma, Qatar Computing Research Institute and North Carolina State University

Sudharshan S. Vazhkudai, Oak Ridge National Laboratory

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BibTeX
@inproceedings {179861,
author = {Yang Liu and Raghul Gunasekaran and Xiaosong Ma and Sudharshan S. Vazhkudai},
title = {Automatic {Identification} of Application {I/O} Signatures from Noisy {Server-Side} Traces},
booktitle = {12th USENIX Conference on File and Storage Technologies (FAST 14)},
year = {2014},
isbn = {ISBN 978-1-931971-08-9},
address = {Santa Clara, CA},
pages = {213--228},
url = {https://www.usenix.org/conference/fast14/technical-sessions/presentation/liu},
publisher = {USENIX Association},
month = feb
}
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