Adopting a new technology, such as a new storage system, is a complicated process because the supporting ecosystems also have to be changed. As a result, any new technology requires exhaustive performance evaluation to justify the cost of switching. However, synthetic workloads or benchmarks typically cannot completely characterize the actual workload. On the other hand, the time and effort required to obtain an appropriate trace can be prohibitive. This work presents a block-level performance measurement tool for storage systems combined with a trace re-player, a trace characteristics analyzer, and a trace re-generator. This new tool is compatible with several different platforms, including Linux and AIX. The purpose of the tool is to evaluate system performance when executing a given application, and to help users determine which system best fits their specific application. Additionally, the trace analyzer can provide details about the characteristics of a given trace. Using the trace analysis results, the re-generator can produce arbitrarily long I/O traces to improve the accuracy of the performance evaluation. The tool also can be used to determine whether a particular system can be adapted to a specific application, and to make comparisons between systems.
|Original language||English (US)|
|Title of host publication||2017 IEEE International Conference on Networking, Architecture, and Storage, NAS 2017 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|State||Published - Sep 6 2017|
|Event||2017 IEEE International Conference on Networking, Architecture, and Storage, NAS 2017 - Shenzhen, China|
Duration: Aug 7 2017 → Aug 9 2017
|Name||2017 IEEE International Conference on Networking, Architecture, and Storage, NAS 2017 - Proceedings|
|Other||2017 IEEE International Conference on Networking, Architecture, and Storage, NAS 2017|
|Period||8/7/17 → 8/9/17|
Bibliographical noteFunding Information:
VIII. ACKNOWLEDGMENT This work was supported in part by the Center for Research in Intelligent Storage (CRIS), which is supported by National Science Foundation grant no. IIP-1439622 and member companies. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.
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