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Watch Meta’s engineers discuss optimizing large-scale networks

Engineering at Meta

Also, the pivot to metaverse has led to a significant increase in AI, HPC, and machine learning workloads that demand huge networking bandwidth and compute capacity and pose challenges around safe co-existence of existing web, legacy and modern workloads.

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Introduction to Micro-BFD ( BFD over Port channel)

The Network DNA

Introduction to Micro-BFD ( BFD over Port channel) Micro BFD sessions are those that run on member links of the port channel. Micro BFD sessions are available for both LACP and non-LACP-based port channels. This approach provides faster failure detection because BFD sessions are formed on individual port-channel interfaces.

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A RoCE network for distributed AI training at scale

Engineering at Meta

We ensure that there is enough ingress bandwidth on the rack switch to not hinder the training workload. The BE is a specialized fabric that connects all RDMA NICs in a non-blocking architecture, providing high bandwidth, low latency, and lossless transport between any two GPUs in the cluster, regardless of their physical location.

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OCP Summit 2024: The open future of networking hardware for AI

Engineering at Meta

DSF-based fabrics allow us to build large, non-blocking fabrics to support high-bandwidth AI clusters. Tbps with 64x OSFP ports, and the design is optimized without the need of retimers to achieve maximum power efficiency. The post OCP Summit 2024: The open future of networking hardware for AI appeared first on Engineering at Meta.

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Cato SASE Cloud: Enjoy Simplified Configuration and Centralized, Global Policy Delivery

CATO Networks

Because of this convergence, automated security engines and customized policies benefit from shared context and visibility allowing true single-pass processing and more accurate security verdicts. Customers can control the use of TCP acceleration and Packet Loss Mitigation and assign a bandwidth priority level to the traffic.

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SNMP vs. NetFlow

Kentik

This includes port, IP source, destination, port numbers, and other markings such as quality of service (QoS). SNMP data is also used by network engineers to troubleshoot reported problems along with network architects to do things like capacity planning.

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Juniper Networks selected for radio astronomy project

DCNN Magazine

telescope, supported by Juniper infrastructure, will give ASTRON a factor 10 increase in the network bandwidth available at each LOFAR station. Juniper’s solutions are instrumental in enabling ASTRON to meet the increasing demand for bandwidth and to provide the new era of digital services within the astronomical discovery sector.

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