Scientific and high-performance computing at FAIR
- Future FAIR experiments have to deal with very high input rates, large track multiplicities, make full event reconstruction and selection on-line on a large dedicated computer farm equipped with heterogeneous many-core CPU/GPU compute nodes. To develop efficient and fast algorithms, which are optimized for parallel computations, is a challenge for the groups of experts dealing with the HPC computing. Here we present and discuss the status and perspectives of the data reconstruction and physics analysis software of one of the future FAIR experiments, namely, the CBM experiment.
Download full text files
Additional Services
| Author: | Ivan KiselORCiDGND |
|---|---|
| URN: | urn:nbn:de:hebis:30:3-714529 |
| DOI: | https://doi.org/10.1051/epjconf/20159501007 |
| ISSN: | 2100-014X |
| Parent Title (English): | EPJ Web of Conferences |
| Publisher: | EDP Sciences |
| Place of publication: | Les Ulis |
| Document Type: | Article |
| Language: | English |
| Date of Publication (online): | 2015/05/29 |
| Date of first Publication: | 2015/05/29 |
| Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
| Contributing Corporation: | International Conference on New Frontiers in Physics (3. : 2014 : Crete) |
| Release Date: | 2023/01/31 |
| Volume: | 95 |
| Issue: | 01007 |
| Page Number: | 16 |
| HeBIS-PPN: | 50573754X |
| Institutes: | Physik / Physik |
| Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS) | |
| Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik |
| Sammlungen: | Universitätspublikationen |
| Licence (German): |  Creative Commons - Namensnennung 4.0 |
