Difference between revisions of "Enhanced Adaptive Compression in Lustre"

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   * [https://wr.informatik.uni-hamburg.de/research/projects/ipcc-l/start Scientific Computing Group]
   * [https://wr.informatik.uni-hamburg.de/research/projects/ipcc-l/start Scientific Computing Group]
   * [https://jira.whamcloud.com/browse/LU-10026]
   * [https://jira.whamcloud.com/browse/LU-10026 Jira]

Latest revision as of 03:43, 7 March 2019

General Information

Due to the increasing gap between computational speed, network speed and storage capacity, it has become necessary to investigate data reduction techniques. Storage systems have become a significant part of the total cost of ownership due to the increased amount of storage devices, their associated acquisition cost and energy consumption.

Ultimately, we are aiming for compression support in Lustre at multiple levels:

 - Client-side compression allows using the available network and storage capacity more efficiently,
 - Client hints empower applications to provide information useful for compression and
 - Adaptive compression makes it possible to choose appropriate settings depending on performance metrics and projected benefits.

Compression will be completely transparent to the applications because it will be performed by the client and/or server on their behalf. However, it will be possible for users to tune Lustre's behavior to obtain the best performance/compression/etc. When using client-side compression, the single stream performance bottleneck will directly benefit from the compression.


Intel Parallel Computing Center for Lustre Universität Hamburg “Enhanced Adaptive Compression in Lustre”

Project Links
 * Scientific Computing Group
 * Jira