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- Publisher Website: 10.1145/3477132.3483583
- Scopus: eid_2-s2.0-85119095945
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Conference Paper: Automated SmartNIC Offloading Insights for Network Functions
| Title | Automated SmartNIC Offloading Insights for Network Functions |
|---|---|
| Authors | |
| Keywords | Machine learning Network function SmartNIC |
| Issue Date | 2021 |
| Citation | Sosp 2021 Proceedings of the 28th ACM Symposium on Operating Systems Principles, 2021, p. 772-787 How to Cite? |
| Abstract | The gap between CPU and networking speeds has motivated the development of SmartNICs for NF (network functions) offloading. However, offloading performance is predicated upon intricate knowledge about SmartNIC hardware and careful hand-tuning of the ported programs. Today, developers cannot easily reason about the offloading performance or the effectiveness of different porting strategies without resorting to a trial-and-error approach. Clara is an automated tool that improves the productivity of this workflow by generating offloading insights. Our tool can a) analyze a legacy NF in its unported form, predicting its performance characteristics on a SmartNIC (e.g., compute vs. memory intensity); and b) explore and suggest porting strategies for the given NF to achieve higher performance. To achieve these goals, Clara uses program analysis techniques to extract NF features, and combines them with machine learning techniques to handle opaque SmartNIC details. Our evaluation using Click NF programs on a Netronome Smart-NIC shows that Clara achieves high accuracy in its analysis, and that its suggested porting strategies lead to significant performance improvements. |
| Persistent Identifier | http://hdl.handle.net/10722/363427 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Qiu, Yiming | - |
| dc.contributor.author | Xing, Jiarong | - |
| dc.contributor.author | Hsu, Kuo Feng | - |
| dc.contributor.author | Kang, Qiao | - |
| dc.contributor.author | Liu, Ming | - |
| dc.contributor.author | Narayana, Srinivas | - |
| dc.contributor.author | Chen, Ang | - |
| dc.date.accessioned | 2025-10-10T07:46:47Z | - |
| dc.date.available | 2025-10-10T07:46:47Z | - |
| dc.date.issued | 2021 | - |
| dc.identifier.citation | Sosp 2021 Proceedings of the 28th ACM Symposium on Operating Systems Principles, 2021, p. 772-787 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/363427 | - |
| dc.description.abstract | The gap between CPU and networking speeds has motivated the development of SmartNICs for NF (network functions) offloading. However, offloading performance is predicated upon intricate knowledge about SmartNIC hardware and careful hand-tuning of the ported programs. Today, developers cannot easily reason about the offloading performance or the effectiveness of different porting strategies without resorting to a trial-and-error approach. Clara is an automated tool that improves the productivity of this workflow by generating offloading insights. Our tool can a) analyze a legacy NF in its unported form, predicting its performance characteristics on a SmartNIC (e.g., compute vs. memory intensity); and b) explore and suggest porting strategies for the given NF to achieve higher performance. To achieve these goals, Clara uses program analysis techniques to extract NF features, and combines them with machine learning techniques to handle opaque SmartNIC details. Our evaluation using Click NF programs on a Netronome Smart-NIC shows that Clara achieves high accuracy in its analysis, and that its suggested porting strategies lead to significant performance improvements. | - |
| dc.language | eng | - |
| dc.relation.ispartof | Sosp 2021 Proceedings of the 28th ACM Symposium on Operating Systems Principles | - |
| dc.subject | Machine learning | - |
| dc.subject | Network function | - |
| dc.subject | SmartNIC | - |
| dc.title | Automated SmartNIC Offloading Insights for Network Functions | - |
| dc.type | Conference_Paper | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1145/3477132.3483583 | - |
| dc.identifier.scopus | eid_2-s2.0-85119095945 | - |
| dc.identifier.spage | 772 | - |
| dc.identifier.epage | 787 | - |
