Compute engine makers can do all they want to bring the performance of their devices on par or even reasonably close to that of Nvidia’s various GPU accelerators, but until they have something akin to the NVLink and NVSwitch memory fabric that Nvidia uses to leverage the performance of many GPUs at bandwidths that dwarf PCI-Express switches and latencies that dwarf Ethernet interconnects, they can never catch up. …
It is safe to say in 2025 that the best job in the world is the chief executive officer of Nvidia, and that the company’s co-founder, Jensen Huang, has steered the company to great heights as much as fellow co-founders Thomas Watson ever did with International Business Machines, Larry Ellison ever did with Oracle, and Steve Jobs ever did with Apple Computer. …
It has become a well known fact these days that the switches that are used to interconnect distributed systems are not the most expensive part of that network, but rather it is the optical transceivers and fiber optic cables that comprise the bulk of the cost. …
When you are designing applications that run across the scale of an entire datacenter and that are comprised of hundreds to thousands of microservices running on countless individual servers and that have to be called within a matter of microseconds to give the illusion of a monolithic application, building fully connected, high bi-section bandwidth Clos networks is a must. …
Nvidia hit a rare patch of bad news earlier this month when reports started circulating claiming that the company’s much-anticipated “Blackwell” GPU accelerators could be delayed by as much as three months due to design flaws. …
We like datacenter compute engines here at The Next Platform, but as the name implies, what we really like are platforms – how compute, storage, networking, and systems software are brought together to create a platform on which to build applications. …
Note: There is a story called A Tale Of Two Nvidia Eos Supercomputers that augments and corrects information that originally appeared in this story as it was published on February 15. …
Not everybody can afford an Nvidia DGX AI server loaded up with the latest “Hopper” H100 GPU accelerators or even one of its many clones available from the OEMs and ODMs of the world. …
We have been talking about silicon photonics so long that we are, probably like many of you, frustrated that it already is not ubiquitous. …
Normally, when we look at a system, we think from the compute engines at a very fine detail and then work our way out across the intricacies of the nodes and then the interconnect and software stack that scales it across the nodes into a distributed computing platform. …
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