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Article: Efficient low-latency packet processing using On-GPU Thread-Data Remapping

TitleEfficient low-latency packet processing using On-GPU Thread-Data Remapping
Authors
KeywordsPacket processing
Software router
GPU control flow divergence
SIMD
Issue Date2019
PublisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/jpdc
Citation
Journal of Parallel and Distributed Computing, 2019, v. 133, p. 51-62 How to Cite?
AbstractGraphics processing units are widely-used for packet processing acceleration in both physical and virtual networks. However, real-life packets come in highly-divergent sizes, causing severe GPU control flow divergence. Previous solutions rely on CPU preprocessing to reduce divergence, but it forbids the more efficient NIC–GPU packet streaming as packet batches have to stop completely at host machine. To fully utilize both GPU and PCIe resources, we propose Blink as a GPU modular software router. Instead of CPU pre-processing, the Blink router uses On-GPU Thread-Data Remapping to reduce divergence, and our novel Cross-Iteration Thread Event Signaling mechanism filters unnecessary inter-thread synchronization, doubling the performance gain achieved by traditional solution. Serving as a TCP/IP router with Deep Packet Inspection (DPI) firewall, Blink can sustain processing throughput of 31.5 GBit/s over a PCIe bandwidth of 32 GBit/s. Given a certain bandwidth, Blink reduces processing latency at least by half compared with other works.
Persistent Identifierhttp://hdl.handle.net/10722/283322
ISSN
2021 Impact Factor: 4.542
2020 SCImago Journal Rankings: 0.638
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLIN, H-
dc.contributor.authorWang, CL-
dc.date.accessioned2020-06-22T02:55:00Z-
dc.date.available2020-06-22T02:55:00Z-
dc.date.issued2019-
dc.identifier.citationJournal of Parallel and Distributed Computing, 2019, v. 133, p. 51-62-
dc.identifier.issn0743-7315-
dc.identifier.urihttp://hdl.handle.net/10722/283322-
dc.description.abstractGraphics processing units are widely-used for packet processing acceleration in both physical and virtual networks. However, real-life packets come in highly-divergent sizes, causing severe GPU control flow divergence. Previous solutions rely on CPU preprocessing to reduce divergence, but it forbids the more efficient NIC–GPU packet streaming as packet batches have to stop completely at host machine. To fully utilize both GPU and PCIe resources, we propose Blink as a GPU modular software router. Instead of CPU pre-processing, the Blink router uses On-GPU Thread-Data Remapping to reduce divergence, and our novel Cross-Iteration Thread Event Signaling mechanism filters unnecessary inter-thread synchronization, doubling the performance gain achieved by traditional solution. Serving as a TCP/IP router with Deep Packet Inspection (DPI) firewall, Blink can sustain processing throughput of 31.5 GBit/s over a PCIe bandwidth of 32 GBit/s. Given a certain bandwidth, Blink reduces processing latency at least by half compared with other works.-
dc.languageeng-
dc.publisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/jpdc-
dc.relation.ispartofJournal of Parallel and Distributed Computing-
dc.subjectPacket processing-
dc.subjectSoftware router-
dc.subjectGPU control flow divergence-
dc.subjectSIMD-
dc.titleEfficient low-latency packet processing using On-GPU Thread-Data Remapping-
dc.typeArticle-
dc.identifier.emailWang, CL: clwang@cs.hku.hk-
dc.identifier.authorityWang, CL=rp00183-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jpdc.2019.06.009-
dc.identifier.scopuseid_2-s2.0-85067975117-
dc.identifier.hkuros310354-
dc.identifier.volume133-
dc.identifier.spage51-
dc.identifier.epage62-
dc.identifier.isiWOS:000488138800005-
dc.publisher.placeUnited States-
dc.identifier.issnl0743-7315-

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