Cumulus & Apstra Demo on Facebook’s Backpack & Wedge Switches
Facebook shows off the OCP ecosystem at an invitation-only event.
Facebook shows off the OCP ecosystem at an invitation-only event.
We are thrilled to announce our integration with Backpack — the industry’s first commercially supported open chassis with Cumulus Linux. You can now have a consistent operating model across fixed and modular platforms.
With Backpack and Cumulus Linux, you can simplify hyperscaling your network infrastructure, especially as you migrate from 40G to 100G platforms.
When Facebook first approached us about the technology, we were thrilled to be a part of it. We’ve always believed the chassis is an important part of the ecosystem, but we also knew the technology needed to be improved.
In fact, when Cumulus Networks was first founded, we were working on developing a chassis that would work seamlessly with open networking ecosystems. No really, we did! Don’t believe us? Here’s the proof:
Clearly, we never quite got it right. But luckily for us and open networking enthusiasts everywhere, Facebook did. Read more about Facebook and Cumulus Networks.
This is Facebook’s second generation modular switch platform based on web-scale principles. Cumulus Networks collaborated with Facebook to provide ONIE support for Backpack. Backpack is an 8RU chassis with 128x 100G ports built as a distributed model where each line card and fabric card have dedicated CPUs Continue reading
It is the first month of a new year, and this is the time that IBM traditionally does reorganizations of its business lines and plays musical chairs with its executives to reconfigure itself for the coming year. And just like clockwork, late last week the top brass at Big Blue did internal announcements explaining the changes it is making to transform its wares into a platform better suited to the times.
The first big change, and one that may have precipitated all of the others that have been set in place, is Robert LeBlanc, who is the senior vice president …
IBM Reorg Forges Cognitive Systems, Merges Cloud And Analytics was written by Timothy Prickett Morgan at The Next Platform.
In order for operators to execute blended service models successfully, a policy-based and predictive analytics-driven approach to end-to-end service management will be essential.
This balance is also important when looking at the interaction within a server between the network cards (which have some on-board buffering) and the DPDK managed buffer resources on the host. A better tuning of the buffer sizes can eliminate potential packet losses. This paper is summarizing what to do when going from one type of network card to another one that has different on-board buffer behavior. It also has the potential to explain and fix certain packet loss issues going from one generation of a NIC card to another (e.g. when moving from Intel® Ethernet Server Adapter X520 to Intel® Ethernet Controller XL710)
Basically it comes down to configuring the RX descriptors.
So, to avoid packet losses due to CPU core being interrupted when using Fortville (or when using Niantic and SRIOV), the number of RX descriptors should be configured high enough, for instance to 2048.
Wired Ethernet: Intel® Ethernet X520 to XL710 -… |Intel Communities : https://communities.intel.com/community/wired/blog/2017/01/09/intel-ethernet-x520-to-xl710-tuning-the-buffers-a-practical-guide-to-reduce-or-avoid-packet-loss-in-dpdk-applications
Link to local version PDF File for my future self (hi there!)
X520_to_XL710_Tuning_The_Buffers.pdf
The post Research: Wired Ethernet: Intel® Ethernet X520 to XL710 -… |Intel Communities appeared first on EtherealMind.
Software defined infrastructure sprawl is worst where it is compound.
The post Worth Reading: Study highlights lack of IoT security appeared first on 'net work.
Over the last two years, we have highlighted deep learning use cases in enterprise areas including genomics, large-scale business analytics, and beyond, but there are still many market areas that are still building a profile for where such approaches fit into existing workflows. Even though model training and inference might be useful, for some areas that have complex simulation-driven workflows, there are great efficiencies that could come from deep neural nets, but integrating those elements is difficult.
The oil and gas industry is one area where deep learning holds promise, at least in theory. For some steps in the resource …
Refining Oil and Gas Discovery with Deep Learning was written by Nicole Hemsoth at The Next Platform.