Fast CSV Loading Using GPUs and RDMA for In-Memory Data Processing
| dc.contributor.author | Kumaigorodski, Alexander | |
| dc.contributor.author | Lutz, Clemens | |
| dc.contributor.author | Markl, Volker | |
| dc.contributor.editor | Kai-Uwe Sattler | |
| dc.contributor.editor | Melanie Herschel | |
| dc.contributor.editor | Wolfgang Lehner | |
| dc.date.accessioned | 2021-03-16T07:57:09Z | |
| dc.date.available | 2021-03-16T07:57:09Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Comma-separated values (CSV) is a widely-used format for data exchange. Due to the format's prevalence, virtually all industrial-strength database systems and stream processing frameworks support importing CSV input. However, loading CSV input close to the speed of I/O hardware is challenging. Modern I/O devices such as InfiniBand NICs and NVMe SSDs are capable of sustaining high transfer rates of 100 Gbit/s and higher. At the same time | en |
| dc.identifier.doi | 10.18420/btw2021-01 | |
| dc.identifier.isbn | 978-3-88579-705-0 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/35792 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik, Bonn | |
| dc.relation.ispartof | BTW 2021 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-311 | |
| dc.subject | CSV | |
| dc.subject | Parsing | |
| dc.subject | GPU | |
| dc.subject | CUDA | |
| dc.subject | RDMA | |
| dc.subject | InfiniBand | |
| dc.title | Fast CSV Loading Using GPUs and RDMA for In-Memory Data Processing | en |
| gi.citation.endPage | 38 | |
| gi.citation.startPage | 19 | |
| gi.conference.date | 13.-17. September 2021 | |
| gi.conference.location | Dresden | |
| gi.conference.sessiontitle | Database Technology |
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