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Design of a Message Passing Model for Use in a Heterogeneous CPU-NFP Framework for Network Analytics

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dc.contributor.author Pennefather, S
dc.contributor.author Bradshaw, K
dc.contributor.author Irwin, Barry VW
dc.date.accessioned 2017-11-15T12:33:33Z
dc.date.available 2017-11-15T12:33:33Z
dc.date.issued 2017-09
dc.identifier.citation Pennefather, S., Bradshaw, K. and Irwin, B.V.W. 2017. Design of a Message Passing Model for Use in a Heterogeneous CPU-NFP Framework for Network Analytics. Southern Africa Telecommunication Networks and Applications Conference (SATNAC) 2017, 3-10 September 2017, Freedom of the Seas, Royal Caribbean International, Barcelona, Spain en_US
dc.identifier.isbn 978-0-620-76756-9
dc.identifier.uri http://www.satnac.org.za//proceedings/2017/SATNAC%202017%20Proceedings%20Final.pdf
dc.identifier.uri http://hdl.handle.net/10204/9784
dc.description Paper presented at the Southern Africa Telecommunication Networks and Applications Conference (SATNAC) 2017, 3-10 September 2017, Freedom of the Seas, Royal Caribbean International, Barcelona, Spain en_US
dc.description.abstract Currently, network analytics requires direct access to network packets, normally through a third-party application, which means that obtaining realtime results is difficult. We propose the NFP-CPU heterogeneous framework to allow parts of applications written in the Go programming language to be executed on a Network Flow Processor (NFP) for enhanced performance. This paper explores the need and feasibility of implementing a message passing model for data transmission between the NFP and CPU, which is the crux of such a heterogeneous framework. Architectural differences between the two domains are highlighted within this context and we present a solution to bridging these differences. en_US
dc.language.iso en en_US
dc.publisher SATNAC en_US
dc.relation.ispartofseries Worklist;19657
dc.subject Heterogeneous Computing en_US
dc.subject Network Processor en_US
dc.subject Network Analytics en_US
dc.title Design of a Message Passing Model for Use in a Heterogeneous CPU-NFP Framework for Network Analytics en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Pennefather, S., Bradshaw, K., & Irwin, B. V. (2017). Design of a Message Passing Model for Use in a Heterogeneous CPU-NFP Framework for Network Analytics. SATNAC. http://hdl.handle.net/10204/9784 en_ZA
dc.identifier.chicagocitation Pennefather, S, K Bradshaw, and Barry VW Irwin. "Design of a Message Passing Model for Use in a Heterogeneous CPU-NFP Framework for Network Analytics." (2017): http://hdl.handle.net/10204/9784 en_ZA
dc.identifier.vancouvercitation Pennefather S, Bradshaw K, Irwin BV, Design of a Message Passing Model for Use in a Heterogeneous CPU-NFP Framework for Network Analytics; SATNAC; 2017. http://hdl.handle.net/10204/9784 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Pennefather, S AU - Bradshaw, K AU - Irwin, Barry VW AB - Currently, network analytics requires direct access to network packets, normally through a third-party application, which means that obtaining realtime results is difficult. We propose the NFP-CPU heterogeneous framework to allow parts of applications written in the Go programming language to be executed on a Network Flow Processor (NFP) for enhanced performance. This paper explores the need and feasibility of implementing a message passing model for data transmission between the NFP and CPU, which is the crux of such a heterogeneous framework. Architectural differences between the two domains are highlighted within this context and we present a solution to bridging these differences. DA - 2017-09 DB - ResearchSpace DP - CSIR KW - Heterogeneous Computing KW - Network Processor KW - Network Analytics LK - https://researchspace.csir.co.za PY - 2017 SM - 978-0-620-76756-9 T1 - Design of a Message Passing Model for Use in a Heterogeneous CPU-NFP Framework for Network Analytics TI - Design of a Message Passing Model for Use in a Heterogeneous CPU-NFP Framework for Network Analytics UR - http://hdl.handle.net/10204/9784 ER - en_ZA


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