|Name:||(12) SIOX: An Infrastructure for Monitoring and Optimization of HPC-I/O|
|Time:||Monday, June 23, 2014
05:39 pm - 05:46 pm
CCL - Congress Center Leipzig
|Speaker:||Michaela Zimmer, University of Hamburg|
|Abstract:||Performance analysis and optimization of high-performance I/O systems is a daunting task.
Mainly, this is due to the overwhelmingly complex interplay of the involved hardware and software layers. The Scalable I/O for Extreme Performance (SIOX) project provides a versatile environment for monitoring I/O activities and learning from this information. The goal of SIOX is to automatically suggest and apply performance optimizations, and to assist in locating and diagnosing performance problems.
In this poster, we present the current status of SIOX. Our modular architecture covers instrumentation of POSIX, MPI and other high-level I/O libraries; the monitoring data is recorded asynchronously into a global database, and recorded traces can be visualized. Furthermore, we offer a set of primitive plug-ins with additional features to demonstrate the flexibility of our architecture:
A surveyor plug-in to keep track of the observed spatial access patterns;
an fadvise plug-in for injecting hints to achieve read-ahead for strided access patterns;
and an optimizer plug-in which monitors the performance achieved with different MPI-IO hints, automatically supplying the best known hint-set when no hints were explicitly set.
The presentation of the technical status is accompanied by a demonstration of some of these features on our 20 node cluster. In additional experiments, we analyze the overhead for concurrent access, for MPI-IO's 4-levels of access, and for an instrumented climate application. While our prototype is not yet full-featured, it demonstrates the potential and feasibility of our approach.
Julian Kunkel, Universität Hamburg; Michaela Zimmer, Universität Hamburg; Marc Christopher Wiedemann, Universität Hamburg; Nathanael Hübbe, Universität Hamburg; Alvaro Aguilera, TU Dresden; Holger Mickler, TU Dresden; Xuan Wang, HLRS; Andrij Chut, HLRS; Thomas Bönisch, HLRS