Software-Defined Storage for Fast Trajectory Queries using a DeltaFS Indexed Massive Directory

PDSW-DISCS 2017: 2nd Joint International Workshop on Parallel Data Storage and Data Intensive Scalable Computing Systems held in conjunction with SC17, Denver, CO, 2017.

Qing Zheng*, George Amvrosiadis*, Saurabh Kadekodi*, Garth A. Gibson*, Charles D. Cranor*, Bradley W. Settlemyer†, Gary Grider†, Fan Guo†

* Carnegie Mellon University
† Los Alamos National Laboratory


In this paper we introduce the Indexed Massive Directory, a new technique for indexing data within DeltaFS. With its design as a scalable, server-less file system for HPC platforms, DeltaFS scales file system metadata performance with application scale. The Indexed Massive Directory is a novel extension to the DeltaFS data plane, enabling in-situ indexing of massive amounts of data written to a single directory simultaneously, and in an arbitrarily large number of files. We achieve this through a memory-efficient indexing mechanism for reordering and indexing data, and a log-structured storage layout to pack small writes into large log objects, all while ensuring compute node resources are used frugally. We demonstrate the efficiency of this indexing mechanism through VPIC, a widely-used simulation code that scales to trillions of particles. With DeltaFS, we modify VPIC to create a file for each particle to receive writes of that particle’s output data. Dynamically indexing the directory’s underlying storage allows us to achieve a 5000x speedup in single particle trajectory queries, which require reading all data for a single particle. This speedup increases with application scale while the overhead is fixed at 3% of available memory.

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