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X-WR-CALDESC:Events for P4 - Language Consortium
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DTSTART;TZID=UTC:20210823T100000
DTEND;TZID=UTC:20210827T170000
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SUMMARY:ACM SIGCOMM 2021
DESCRIPTION:ONF projects are being highlighted in several of the ACM SIGCOMM 2021 sessions: \nAugust 23\, 2021 | 10:00am – 5:00pm EDT\nHackathon: P4 on Raspberry PI (P4Pi) \nP4PI enables designing and deploying P4-based network devices using the Raspberry Pi platform and is based on the T4P4S compiler. P4PI is developed as part of the P4 Education Workgroup activities. The team aims to provide both educators and practitioners the knowledge and tools required to use P4PI in class and at home\, including tutorials\, sample code\, tools and community support. \nCheck out the web page to learn more. Introductory videos can be accessed in a YouTube playlist. \nAugust 23\, 2021 | 1:40pm – 5:00pm EDT\nTutorial\, “5G Connected Edge Cloud” \n\nDescribe 5G\, breaking it down into components familiar to the SIGCOMM community.\nIntroduce the available open source software that implements these components.\nShow how these building blocks can be assembled into a Kubernetes-based edge cloud.\nIdentify and discuss the systems research opportunities such a platform enables.\n\nCheck out the web page to learn more. \nAugust 27\, 2021 | 1:00pm – 5:00pm EDT\nTutorial: Network-Accelerated Distributed Deep Learning \n\nAn introduction on scaling distributed machine learning from a networking-centric perspective. Includes a walk through of through of different solutions for accelerating network communication beginning with in-network aggregation\, describing SwitchML (a system for distributed machine learning that accelerates data-parallel training using P4 switches) as an example of co-design of programmable switch-based processing and end-host protocols.\nExamination of into properties of the traffic and exploit the sparsity of gradient values. A description of OmniReduce\, which evolves the concept of in-network aggregation and focuses on efficient collective operations for sparse data. We will close with lossy gradient compression techniques and the GRACE framework for implementing them.\n\nCheck out the web page to learn more.
URL:https://p4.org/event/acm-sigcomm-2021/
CATEGORIES:Events
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