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Adaptive hybrid storage systems leveraging SSDs and HDDs in HPC cloud environments
Authors:Donghun?Koo,Jik-Soo?Kim,Soonwook?Hwang,Hyeonsang?Eom,Jaehwan?Lee  author-information"  >  author-information__contact u-icon-before"  >  mailto:jlee@kau.ac.kr"   title="  jlee@kau.ac.kr"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author  author-information__orcid u-icon-before icon--orcid u-icon-no-repeat"  >  http://orcid.org/---"   itemprop="  url"   title="  View OrcID profile"   target="  _blank"   rel="  noopener"   data-track="  click"   data-track-action="  OrcID"   data-track-label="  "  >View author&#  s OrcID profile
Affiliation:1.School of Electronics and Information Engineering,Korea Aerospace University,Goyang,Republic of Korea;2.Department of Computer Engineering,Myongji University,Yongin,Republic of Korea;3.Korea Institute of Science and Technology Information,Daejeon,Republic of Korea;4.Department of Computer Science and Engineering,Seoul National University,Seoul,Republic of Korea
Abstract:Cloud computing should inherently support various types of data-intensive workloads with different storage access patterns. This makes a high-performance storage system in the Cloud an important component. Emerging flash device technologies such as solid state drives (SSDs) are a viable choice for building high performance computing (HPC) cloud storage systems to address more fine-grained data access patterns. However, the bit-per-dollar SSD price is still higher than the prices of HDDs. This study proposes an optimized progressive file layout (PFL) method to leverage the advantages of SSDs in a parallel file system such as Lustre so that small file I/O performance can be significantly improved. A PFL can dynamically adjust chunk sizes and stripe patterns according to various I/O traffics. Extensive experimental results show that this approach (i.e. building a hybrid storage system based on a combination of SSDs and HDDs) can actually achieve balanced throughput over mixed I/O workloads consisting of large and small file access patterns.
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