Kundel, Ralf ; Anderweit, Leonard ; Markussen, Jonas ; Griwodz, Carsten ; Abboud, Osama ; Becker, Benjamin ; Meuser, Tobias (2022)
Host Bypassing: Let your GPU speak Ethernet.
8th International Conference on Network Softwarization. Milano, Italy (27.06.-01.07.2022)
doi: 10.1109/NetSoft54395.2022.9844090
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Hardware acceleration of network functions is essential to meet the challenging Quality of Service requirements in nowadays computer networks. Graphical Processing Units (GPU) are a widely deployed technology that can also be used for computing tasks, including acceleration of network functions. In this work, we demonstrate how commodity GPUs, which do not provide any network interfaces, can be used to accelerate network functions. Our approach leverages PCIe peer-to-peer capabilities and allows the GPU to control the network interface card directly, without any assistance from the operating system or control application. The presented evaluation results demonstrate the feasibility of our approach and its performance of up to 10 Gbit/s, even for small packets.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Kundel, Ralf ; Anderweit, Leonard ; Markussen, Jonas ; Griwodz, Carsten ; Abboud, Osama ; Becker, Benjamin ; Meuser, Tobias |
| Art des Eintrags: | Bibliographie |
| Titel: | Host Bypassing: Let your GPU speak Ethernet |
| Sprache: | Englisch |
| Publikationsjahr: | 3 August 2022 |
| Verlag: | IEEE |
| Buchtitel: | 2022 IEEE 8th International Conference on Network Softwarization (NetSoft) |
| Veranstaltungstitel: | 8th International Conference on Network Softwarization |
| Veranstaltungsort: | Milano, Italy |
| Veranstaltungsdatum: | 27.06.-01.07.2022 |
| DOI: | 10.1109/NetSoft54395.2022.9844090 |
| Kurzbeschreibung (Abstract): | Hardware acceleration of network functions is essential to meet the challenging Quality of Service requirements in nowadays computer networks. Graphical Processing Units (GPU) are a widely deployed technology that can also be used for computing tasks, including acceleration of network functions. In this work, we demonstrate how commodity GPUs, which do not provide any network interfaces, can be used to accelerate network functions. Our approach leverages PCIe peer-to-peer capabilities and allows the GPU to control the network interface card directly, without any assistance from the operating system or control application. The presented evaluation results demonstrate the feasibility of our approach and its performance of up to 10 Gbit/s, even for small packets. |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik > Multimedia Kommunikation |
| Hinterlegungsdatum: | 04 Mai 2023 08:58 |
| Letzte Änderung: | 01 Aug 2023 09:30 |
| PPN: | 510059155 |
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