Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Scaling Dalton, a molecular electronic structure program
KTH, School of Computer Science and Communication (CSC), Centres, Centre for High Performance Computing, PDC.ORCID iD: 0000-0001-9693-6265
KTH, School of Computer Science and Communication (CSC), Centres, Centre for High Performance Computing, PDC.ORCID iD: 0000-0002-5415-1248
KTH, School of Biotechnology (BIO), Theoretical Chemistry and Biology. KTH, School of Computer Science and Communication (CSC), Centres, Centre for High Performance Computing, PDC.ORCID iD: 0000-0002-9123-8174
Barcelona Supercomputing Center, Universitat Politecnica de Catalunya, Barcelona, Spain.
Show others and affiliations
2011 (English)In: Seventh International Conference on e-Science, e-Science 2011, 5-8 December 2011, Stockholm, Sweden, IEEE conference proceedings, 2011, 256-262 p.Conference paper, Published paper (Refereed)
Abstract [en]

Dalton is a molecular electronic structure program featuring common methods of computational chemistry that are based on pure quantum mechanics (QM) as well as hybrid quantum mechanics/molecular mechanics (QM/MM). It is specialized and has a leading position in calculation of molecular properties with a large world-wide user community (over 2000 licenses issued). In this paper, we present a characterization and performance optimization of Dalton that increases the scalability and parallel efficiency of the application. We also propose asolution that helps to avoid the master/worker design of Daltonto become a performance bottleneck for larger process numbers and increase the parallel efficiency.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2011. 256-262 p.
Keyword [en]
Chemistry, Image color analysis, Libraries, Measurement, Optimization, Quantum mechanics, Wave functions
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-50421DOI: 10.1109/eScience.2011.43Scopus ID: 2-s2.0-84856350618ISBN: 978-1-4577-2163-2 (print)OAI: oai:DiVA.org:kth-50421DiVA: diva2:461904
Conference
Seventh International Conference on e-Science, e-Science 2011, 5-8 December 2011, Stockholm, Sweden
Funder
Swedish e‐Science Research Center, OpCoReSEU, FP7, Seventh Framework Programme, INFSO RI-261523Swedish e‐Science Research Center
Note
Copyright 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. QC 20120110Available from: 2012-01-10 Created: 2011-12-05 Last updated: 2015-05-08Bibliographically approved
In thesis
1. Towards Scalable Performance Analysis of MPI Parallel Applications
Open this publication in new window or tab >>Towards Scalable Performance Analysis of MPI Parallel Applications
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

  A considerably fraction of science discovery is nowadays relying on computer simulations. High Performance Computing  (HPC) provides scientists with the means to simulate processes ranging from climate modeling to protein folding. However, achieving good application performance and making an optimal use of HPC resources is a heroic task due to the complexity of parallel software. Therefore, performance tools  and runtime systems that help users to execute  applications in the most optimal way are of utmost importance in the landscape of HPC.  In this thesis, we explore different techniques to tackle the challenges of collecting, storing, and using  fine-grained performance data. First, we investigate the automatic use of real-time performance data in order to run applications in an optimal way. To that end, we present a prototype of an adaptive task-based runtime system that uses real-time performance data for task scheduling. This runtime system has a performance monitoring component that provides real-time access to the performance behavior of anapplication while it runs. The implementation of this monitoring component is presented and evaluated within this thesis. Secondly, we explore lossless compression approaches  for MPI monitoring. One of the main problems that  performance tools face is the huge amount of fine-grained data that can be generated from an instrumented application. Collecting fine-grained data from a program is the best method to uncover the root causes of performance bottlenecks, however, it is unfeasible with extremely parallel applications  or applications with long execution times. On the other hand, collecting coarse-grained data is scalable but  sometimes not enough to discern the root cause of a performance problem. Thus, we propose a new method for performance monitoring of MPI programs using event flow graphs. Event flow graphs  provide very low overhead in terms of execution time and  storage size, and can be used to reconstruct fine-grained trace files of application events ordered in time.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. viii, 39 p.
Series
TRITA-CSC-A, ISSN 1653-5723 ; 2015:05
Keyword
parallel computing, performance monitoring, performance tools, event flow graphs
National Category
Computer Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:kth:diva-165043 (URN)978-91-7595-518-6 (ISBN)
Presentation
2015-05-20, The Visualization Studio, room 4451, Lindstedtsvägen 5, KTH, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20150508

Available from: 2015-05-08 Created: 2015-04-21 Last updated: 2015-05-08Bibliographically approved

Open Access in DiVA

fulltext(451 kB)376 downloads
File information
File name FULLTEXT01.pdfFile size 451 kBChecksum SHA-512
205766fc49eb230f03c4069e7eb9537e7a35dd63cd050ec4ebc7fb5b0b0fbd8917606bf77576461fb3bb04dd3e901a42ea8f00ac9b26b3c74860a1d1a53d1363
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopusIEEEXplore

Authority records BETA

Aguilar, XavierSchliephake, MichaelVahtras, OlavLaure, Erwin

Search in DiVA

By author/editor
Aguilar, XavierSchliephake, MichaelVahtras, OlavLaure, Erwin
By organisation
Centre for High Performance Computing, PDCTheoretical Chemistry and Biology
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 376 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 250 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf