For the previous few months, I’ve labored with my colleagues at CommScope to create an Synthetic Intelligence (AI) ordering information to assist our clients and companions to navigate the myriad of structured cabling options accessible. This new world is each thrilling and very dynamic when it comes to know-how selections.
Within the AI business, each day can carry a brand new know-how announcement, a brand new product launch and new predictions from the business press. A few of these developments align to at least one one other, while others can appear to contradict, making it tough for C-suite executives and information heart operations administrators to plan with out second guessing themselves about whether or not they’ve made the correct alternative.
Discussing this enterprise problem with a colleague, they launched me to a poem titled “The Highway Not Taken” by the American poet Robert Lee Frost. In that poem, Frost takes a stroll within the woods. When he involves a fork within the highway, he’s pressured to choose, to comply with both path A or path B.
He can’t see what’s on the finish of both highway; the view is obscured by undergrowth—which means {that a} resolution may solely be primarily based on what they might be seen immediately in entrance of him. Having made a alternative and attending to the tip of the highway, Frost begins to query if he made the correct alternative, or if he would ever have the prospect to revisit the choice and the place the opposite highway might need led him.
I see this situation mirrored within the conversations and questions on AI know-how I hear amongst information heart house owners frequently. They usually ask, what they need to deploy? Will that call assist their firm’s targets? Will their infrastructure be future proofed—and the place can they be taught extra? Like Frost, they’ll’t but see the tip of their proposed path and ponder the implications of their selections primarily based on accessible data.
To assist reply a few of these questions, we created an in depth ordering information known as “Knowledge Middle Cabling Options for NVIDIA AI Networks.” This doc is focused at information heart house owners and operators, community integrators and techniques suppliers. These are the individuals who have duty for making AI information facilities occur, and this doc guides the reader by way of the cabling options (together with optical fiber, twisted pair copper and fiber raceway) which can be important to assembly the calls for for AI computing.
Highlighting CommScope’s options for AI functions in a single doc simplifies the choice course of for a community designer by exhibiting how every of the options work collectively. It additionally defines the place the NVIDIA transceivers are within the community, their interface speeds and the corresponding cabling choices they require.
For additional simplification, we thought laborious about how finest to design the doc for simple navigation, so we made it interactive—enabling the reader to maneuver rapidly and simply by way of every of its sections by way of a instrument bar on the backside of every web page. From right here, you’ll be able to select to navigate by both hyperlink speeds (e.g. 200G, 400G or 800G), or by way of an architectural sort (direct join versus a structured cabling strategy). We additionally included reference designs, giving examples of tips on how to cable an NVIDIA DGX H100 scalable unit (SU), proper as much as the spectacular NVIDIA DGX H100 Tremendous POD.
Whenever you discover a answer and product that matches your particular wants, we’ve offered hyperlinks that can take you immediately from the doc to the product net pages on CommScope.com, the place you could find dwell data and information sheets—which it can save you to mission BoMs that may be constructed utilizing the “My Product Lists” part of our web site.
Recognizing that there’s multiple highway to take, we provide systems-level steering primarily based on our collective experiences and buyer insights from across the globe, together with:
- The pliability that may be delivered to your networking spine design by choosing an MPO-16 fiber infrastructure over a legacy MPO-8 system—and the extra densification advantages that this alternative can carry to your pathways across the information corridor and inside information racks.
- How utilizing mesh architectures in your information heart design can assist decreased patching complexity and simplify redundancy planning.
- When extremely low-loss (ULL) techniques can help in migrating to increased information fee functions in an AI community.
- Why selecting FiberGuide® optical raceway is a necessary instrument to assist the distributed nature of networking gear in a power-constrained AI community.
To me, the poem “The Highway Not Taken” captures the present dilemma that many within the AI information heart development business face, that’s, that selections must be made that are by no means straightforward, particularly if the view of both highway will not be clear, and that the chance to revisit your resolution might not be potential. My recommendation is to decide on your companions nicely, a trusted accomplice who has travelled many roads, one which has the expertise to clarify the implications of taking one resolution over one other.
Lastly, take a information with you that may give prompt entry to the kind of element that you simply’re going to wish to simplify your AI journey. Obtain our information: Knowledge Middle Cabling Answer for NVIDIA AI Networks, right here.
And remember to take a look at our Generative AI sources and articles right here, the place we commonly present contemporary perception and up to date content material in regards to the topic.
For the previous few months, I’ve labored with my colleagues at CommScope to create an Synthetic Intelligence (AI) ordering information to assist our clients and companions to navigate the myriad of structured cabling options accessible. This new world is each thrilling and very dynamic when it comes to know-how selections.
Within the AI business, each day can carry a brand new know-how announcement, a brand new product launch and new predictions from the business press. A few of these developments align to at least one one other, while others can appear to contradict, making it tough for C-suite executives and information heart operations administrators to plan with out second guessing themselves about whether or not they’ve made the correct alternative.
Discussing this enterprise problem with a colleague, they launched me to a poem titled “The Highway Not Taken” by the American poet Robert Lee Frost. In that poem, Frost takes a stroll within the woods. When he involves a fork within the highway, he’s pressured to choose, to comply with both path A or path B.
He can’t see what’s on the finish of both highway; the view is obscured by undergrowth—which means {that a} resolution may solely be primarily based on what they might be seen immediately in entrance of him. Having made a alternative and attending to the tip of the highway, Frost begins to query if he made the correct alternative, or if he would ever have the prospect to revisit the choice and the place the opposite highway might need led him.
I see this situation mirrored within the conversations and questions on AI know-how I hear amongst information heart house owners frequently. They usually ask, what they need to deploy? Will that call assist their firm’s targets? Will their infrastructure be future proofed—and the place can they be taught extra? Like Frost, they’ll’t but see the tip of their proposed path and ponder the implications of their selections primarily based on accessible data.
To assist reply a few of these questions, we created an in depth ordering information known as “Knowledge Middle Cabling Options for NVIDIA AI Networks.” This doc is focused at information heart house owners and operators, community integrators and techniques suppliers. These are the individuals who have duty for making AI information facilities occur, and this doc guides the reader by way of the cabling options (together with optical fiber, twisted pair copper and fiber raceway) which can be important to assembly the calls for for AI computing.
Highlighting CommScope’s options for AI functions in a single doc simplifies the choice course of for a community designer by exhibiting how every of the options work collectively. It additionally defines the place the NVIDIA transceivers are within the community, their interface speeds and the corresponding cabling choices they require.
For additional simplification, we thought laborious about how finest to design the doc for simple navigation, so we made it interactive—enabling the reader to maneuver rapidly and simply by way of every of its sections by way of a instrument bar on the backside of every web page. From right here, you’ll be able to select to navigate by both hyperlink speeds (e.g. 200G, 400G or 800G), or by way of an architectural sort (direct join versus a structured cabling strategy). We additionally included reference designs, giving examples of tips on how to cable an NVIDIA DGX H100 scalable unit (SU), proper as much as the spectacular NVIDIA DGX H100 Tremendous POD.
Whenever you discover a answer and product that matches your particular wants, we’ve offered hyperlinks that can take you immediately from the doc to the product net pages on CommScope.com, the place you could find dwell data and information sheets—which it can save you to mission BoMs that may be constructed utilizing the “My Product Lists” part of our web site.
Recognizing that there’s multiple highway to take, we provide systems-level steering primarily based on our collective experiences and buyer insights from across the globe, together with:
- The pliability that may be delivered to your networking spine design by choosing an MPO-16 fiber infrastructure over a legacy MPO-8 system—and the extra densification advantages that this alternative can carry to your pathways across the information corridor and inside information racks.
- How utilizing mesh architectures in your information heart design can assist decreased patching complexity and simplify redundancy planning.
- When extremely low-loss (ULL) techniques can help in migrating to increased information fee functions in an AI community.
- Why selecting FiberGuide® optical raceway is a necessary instrument to assist the distributed nature of networking gear in a power-constrained AI community.
To me, the poem “The Highway Not Taken” captures the present dilemma that many within the AI information heart development business face, that’s, that selections must be made that are by no means straightforward, particularly if the view of both highway will not be clear, and that the chance to revisit your resolution might not be potential. My recommendation is to decide on your companions nicely, a trusted accomplice who has travelled many roads, one which has the expertise to clarify the implications of taking one resolution over one other.
Lastly, take a information with you that may give prompt entry to the kind of element that you simply’re going to wish to simplify your AI journey. Obtain our information: Knowledge Middle Cabling Answer for NVIDIA AI Networks, right here.
And remember to take a look at our Generative AI sources and articles right here, the place we commonly present contemporary perception and up to date content material in regards to the topic.
