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Title: Qthreads and On-Node Run time Coordination.


Abstract not provided.

Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: Proposed for presentation at the ECP held January 30 - March 3, 2017 in Knoxville, TN.
Country of Publication:
United States

Citation Formats

Olivier, Stephen Lecler, and Brightwell, Ronald B. Qthreads and On-Node Run time Coordination.. United States: N. p., 2017. Web.
Olivier, Stephen Lecler, & Brightwell, Ronald B. Qthreads and On-Node Run time Coordination.. United States.
Olivier, Stephen Lecler, and Brightwell, Ronald B. Wed . "Qthreads and On-Node Run time Coordination.". United States. doi:.
title = {Qthreads and On-Node Run time Coordination.},
author = {Olivier, Stephen Lecler and Brightwell, Ronald B.},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Feb 01 00:00:00 EST 2017},
month = {Wed Feb 01 00:00:00 EST 2017}

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  • We present a new high precision clock synchronization algorithm designed for large XT4 and XT5 leadership-class machines. The algorithm, which is designed to support OS noise reduction through co-scheduling, is suitable for usage cases requiring low overhead and minimal time deviation between nodes. Unlike most high-precision algorithms which reach their precision in a post-mortem analysis after the application has completed, the new ORNL developed algorithm rapidly provides precise results during runtime. Previous to our work, the leading high-precision clock synchronization algorithms that made results available during runtime relied on probabilistic schemes that are not guaranteed to result in an answer.
  • A cluster of I/O nodes and a parallel file system are often used to provide high-throughput I/O service to a parallel compute cluster. To exploit I/O parallelism parallel file systems stripe file data across the I/O nodes. While this practice is effective in serving asynchronous requests, it may break individual program's spatial locality, which can seriously degrade I/O performance when the I/O nodes concurrently serve synchronous requests from multiple I/O-intensive programs. In this paper we propose a scheme, Orchestrator, to improve the I/O performance of multi-I/O-node systems by orchestrating I/O services among programs when such inter-I/O-node coordination is dynamically determinedmore » to be cost effective. We have implemented IOrchestrator in the PVFS2 parallel file system. Our experiments with representative parallel benchmarks show that IOrchestrator can significantly improve I/O performance - by up to a factor of 2.5 - delivered by a cluster of I/O nodes servicing concurrently-running parallel programs. Notably, we have not observed any scenarios in which the use of IOrchestrator causes significant performance degradation.« less