Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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1.080 Topics available

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2016A multi-slice simulation algorithm for grazing-incidence small-angle X-ray scattering7citations
  • 2013MPQC: Performance Analysis and Optimizationcitations

Places of action

Chart of shared publication
Kumar, Dinesh
1 / 21 shared
Venkatakrishnan, S. V.
1 / 1 shared
Li, Xiaoye S.
1 / 1 shared
Sinha, Sunil K.
1 / 4 shared
Bailey, David
1 / 1 shared
Williams, Samuel
1 / 2 shared
Chart of publication period
2016
2013

Co-Authors (by relevance)

  • Kumar, Dinesh
  • Venkatakrishnan, S. V.
  • Li, Xiaoye S.
  • Sinha, Sunil K.
  • Bailey, David
  • Williams, Samuel
OrganizationsLocationPeople

report

MPQC: Performance Analysis and Optimization

  • Sarje, Abhinav
  • Bailey, David
  • Williams, Samuel
Abstract

MPQC (Massively Parallel Quantum Chemistry) is a widely usedcomputational quantum chemistry code. It is capable of performing a number ofcomputations commonly occurring in quantum chemistry. In order to achieve betterperformance of MPQC, in this report we present a detailed performance analysisof this code. We then perform loop and memory access optimizations, and measureperformance improvements by comparing the performance of the optimized code withthat of the original MPQC code. We observe that the optimized MPQC code achievesa significant improvement in the performance through a better utilization ofvector processing and memory hierarchies.

Topics
  • impedance spectroscopy