@inproceedings{7512b144340f47389c9125978cc245f4,
title = "PaRSEC in practice: Optimizing a legacy chemistry application through distributed task-based execution",
abstract = "Task-based execution has been growing in popularity as a means to deliver a good balance between performance and portability in the post-petascale era. The Parallel Runtime Scheduling and Execution Control (PARSEC) framework is a task-based runtime system that we designed to achieve high performance computing at scale. PARSEC offers a programming paradigm that is different than what has been traditionally used to develop large scale parallel scientific applications. In this paper, we discuss the use of PARSEC to convert a part of the Coupled Cluster (CC) component of the Quantum Chemistry package NWCHEM into a task-based form. We explain how we organized the computation of the CC methods in individual tasks with explicitly defined data dependencies between them and re-integrated the modified code into NWCHEM. We present a thorough performance evaluation and demonstrate that the modified code outperforms the original by more than a factor of two. We also compare the performance of different variants of the modified code and explain the different behaviors that lead to the differences in performance.",
keywords = "DAG, PTG, PaRSEC, Tasks",
author = "Anthony Danalis and Heike Jagode and George Bosilca and Jack Dongarra",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Cluster Computing, CLUSTER 2015 ; Conference date: 08-09-2015 Through 11-09-2015",
year = "2015",
month = oct,
day = "26",
doi = "10.1109/CLUSTER.2015.50",
language = "English",
series = "Proceedings - IEEE International Conference on Cluster Computing, ICCC",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "304--313",
booktitle = "Proceedings - 2015 IEEE International Conference on Cluster Computing, CLUSTER 2015",
}