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Conference Paper: GPUNFV: a GPU-Accelerated NFV System

TitleGPUNFV: a GPU-Accelerated NFV System
Authors
KeywordsService chain
NFV
Micro service
GPU
Issue Date2017
PublisherAssociation for Computing Machinery.
Citation
The 1st Asia-Pacific Workshop on Networking (APNet’17), Hong Kong, 3-4 August 2017 How to Cite?
AbstractThis paper presents GPUNFV, a high-performance NFV system providing flow-level micro services for stateful service chains with Graphics Processing Unit (GPU) acceleration. GPUNFV exploits the massively-parallel processing power ofGPU tomaximize the throughput of theNFV system. Combined with the customized flow handler, GPUNFV achieves a much better throughput than the existing NFV systems. With a carefully designed GPU-based virtualized network function framework, GPUNFV is able to e ciently support both stateful and stateless network functions. We have implemented a number of GPU-based network functions and a preliminary GPUNFV system to demonstrate the flexibility and potential of our design.
Persistent Identifierhttp://hdl.handle.net/10722/243236
ISBN
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYi, X-
dc.contributor.authorDuan, J-
dc.contributor.authorWu, C-
dc.date.accessioned2017-08-25T02:52:02Z-
dc.date.available2017-08-25T02:52:02Z-
dc.date.issued2017-
dc.identifier.citationThe 1st Asia-Pacific Workshop on Networking (APNet’17), Hong Kong, 3-4 August 2017-
dc.identifier.isbn978-1-4503-5244-4-
dc.identifier.urihttp://hdl.handle.net/10722/243236-
dc.description.abstractThis paper presents GPUNFV, a high-performance NFV system providing flow-level micro services for stateful service chains with Graphics Processing Unit (GPU) acceleration. GPUNFV exploits the massively-parallel processing power ofGPU tomaximize the throughput of theNFV system. Combined with the customized flow handler, GPUNFV achieves a much better throughput than the existing NFV systems. With a carefully designed GPU-based virtualized network function framework, GPUNFV is able to e ciently support both stateful and stateless network functions. We have implemented a number of GPU-based network functions and a preliminary GPUNFV system to demonstrate the flexibility and potential of our design.-
dc.languageeng-
dc.publisherAssociation for Computing Machinery.-
dc.relation.ispartofProceedings of APNet’17-
dc.rightsProceedings of APNet’17. Copyright © Association for Computing Machinery.-
dc.rights©ACM, YYYY. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in PUBLICATION, {VOL#, ISS#, (DATE)} http://doi.acm.org/10.1145/nnnnnn.nnnnnn-
dc.subjectService chain-
dc.subjectNFV-
dc.subjectMicro service-
dc.subjectGPU-
dc.titleGPUNFV: a GPU-Accelerated NFV System-
dc.typeConference_Paper-
dc.identifier.emailWu, C: cwu@cs.hku.hk-
dc.identifier.authorityWu, C=rp01397-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1145/3106989.3106990-
dc.identifier.scopuseid_2-s2.0-85054195274-
dc.identifier.hkuros275480-
dc.identifier.isiWOS:000614068500013-

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