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| 001 | 872623 | ||
| 005 | 20210130004236.0 | ||
| 024 | 7 | _ | |a 2128/23823 |2 Handle |
| 037 | _ | _ | |a FZJ-2020-00115 |
| 100 | 1 | _ | |a Morgenstern, Laura |0 P:(DE-Juel1)169856 |b 0 |e Corresponding author |u fzj |
| 111 | 2 | _ | |a Erste Konferenz für ForschungssoftwareentwicklerInnen in Deutschland |g deRSE19 |c Potsdam |d 2019-06-04 - 2019-06-06 |w Germany |
| 245 | _ | _ | |a NUMA-Awareness as a Plug-In |
| 260 | _ | _ | |c 2019 |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a CONFERENCE_POSTER |2 ORCID |
| 336 | 7 | _ | |a Output Types/Conference Poster |2 DataCite |
| 336 | 7 | _ | |a Poster |b poster |m poster |0 PUB:(DE-HGF)24 |s 1578897674_31747 |2 PUB:(DE-HGF) |x After Call |
| 520 | _ | _ | |a Molecular dynamics (MD) has become a vital research method in biochemistry and materials science. GROMACS aims do develop a flexible and unified tool-box in the field of MD simulations. In MD, the fast multipole method (FMM) is used to compute all pairwise long-range interactions between N particles in time O(N). To tackle exascale, MD applications – as well as several other HPCapplications – have to target strong scaling. To meet the according requirements such as synchronization- and latency-awareness, software needs to adopt to specific hardware properties such ascaching and non-uniform memory access (NUMA). This poster shows how we added NUMA-awareness to our C++ tasking framework for fine-grained parallelism with an FMM as use case. However, the poster has an emphasis on separation of concerns through software architecture since the representation of NUMA in software is not only relevant for the FMM but should be reusable by similar applications. |
| 536 | _ | _ | |a 511 - Computational Science and Mathematical Methods (POF3-511) |0 G:(DE-HGF)POF3-511 |c POF3-511 |f POF III |x 0 |
| 536 | _ | _ | |0 G:(DE-Juel1)PHD-NO-GRANT-20170405 |x 1 |c PHD-NO-GRANT-20170405 |a PhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405) |
| 700 | 1 | _ | |a Haensel, David |0 P:(DE-Juel1)161429 |b 1 |u fzj |
| 700 | 1 | _ | |a Beckmann, Andreas |0 P:(DE-Juel1)157750 |b 2 |u fzj |
| 700 | 1 | _ | |a Kabadshow, Ivo |0 P:(DE-Juel1)132152 |b 3 |u fzj |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/872623/files/deRSE.pdf |
| 856 | 4 | _ | |y OpenAccess |x pdfa |u https://juser.fz-juelich.de/record/872623/files/deRSE.pdf?subformat=pdfa |
| 909 | C | O | |o oai:juser.fz-juelich.de:872623 |p openaire |p open_access |p VDB |p driver |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)169856 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)161429 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)157750 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 3 |6 P:(DE-Juel1)132152 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |1 G:(DE-HGF)POF3-510 |0 G:(DE-HGF)POF3-511 |2 G:(DE-HGF)POF3-500 |v Computational Science and Mathematical Methods |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |l Supercomputing & Big Data |
| 914 | 1 | _ | |y 2019 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 980 | 1 | _ | |a FullTexts |
| 980 | _ | _ | |a poster |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
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