A Library for Advanced Datatype Programming
Author:
Affiliation:
1. TU Wien, Faculty of Informatics, Institute of Information Systems, Research Group Parallel Computing, Favoritenstrasse, Vienna, Austria
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2966884.2966904
Reference32 articles.
1. Efficient algorithms for all-to-all communications in multiport message-passing systems
2. Improving the performance of MPI derived datatypes by optimizing memory-access cost
3. A. Carpen-Amarie S. Hunold and J. L. Träff. MPI derived datatypes: Performance expectations and status quo. arXiv:1607.00178 2016. A. Carpen-Amarie S. Hunold and J. L. Träff. MPI derived datatypes: Performance expectations and status quo. arXiv:1607.00178 2016.
4. On the Expected and Observed Communication Performance with MPI Derived Datatypes
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3. Planning for performance: Enhancing achievable performance for MPI through persistent collective operations;Parallel Computing;2019-01
4. Practical, distributed, low overhead algorithms for irregular gather and scatter collectives;Parallel Computing;2018-07
5. On expected and observed communication performance with MPI derived datatypes;Parallel Computing;2017-11
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