While releasing an update to its InferenceX AI inference benchmark test, formerly known as InferenceMax and thus far only having Nvidia and AMD testing systems using it, the analysts SemiAnalysis declared correctly that thus far only Nvidia, AWS, and Google have created rackscale systems that are deployed today, and that …
It has taken three decades for HPC to move to the cloud, and the truth is that a lot of simulation and modeling applications are still coded to run on CPUs. The good news is that the major clouds and some of the smaller ones have tuned up their CPU …
Adding big blocks of SRAM to collections of AI tensor engines, or better still, a waferscale collection of such engines, turbocharges AI inference, as has been shown time and again by AI upstarts Cerebras Systems, SambaNova Systems (which Intel is rumored to have taken a run at late last year), …
When Meta Platforms does a big AI system deal with Nvidia, that usually means that some other open hardware plan that the company had can’t meet an urgent need for compute. This is not the same thing as falling behind schedule, but it has the same effect. We don’t have …
If you want to be in the DRAM and flash memory markets, you had better enjoy rollercoasters. Because the boom-bust cycles in these businesses are true white-knuckle events. Just as the GenAI market was having its ChatGPT mainstreaming moment in November 2022, the buildout in both personal and datacenter infrastructure …
$230.70. That’s it. If you take the $34.6 billion that Arista Networks has made in product revenue since it was founded way back in 2004 by Andy Bechtolsheim, David Cheriton, and Kenneth Duda and divide it by the 150 million cumulative ports that it has shipped (with the product ramp …
It does not happen very often in the history of business that an orthogonal product is invented that almost immediately doubles the revenue pool of a market and has the prospect of tripling it over the next handful of years. But that is precisely what GenAI has done for the …
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It has taken many years for the AI boom to reach the general ledgers and balance sheets of the world’s largest original equipment manufacturers, and one might say that it has taken particularly long for Cisco Systems, the dominant supplier of switching and routing in the enterprise and traditional telco/service …
AI projects don’t fail because models don’t work or GPUs lack performance. They fail because data can’t keep pace. Enterprise teams have foundation models working. They have GPU capacity. But when they try to scale AI across hybrid and multi-cloud environments, data becomes the bottleneck. Distributed data stays fragmented. Real-time …
In the modern AI datacenter – really, a data galaxy at this point because AI processing needs have broken well beyond the bounds of a single datacenter or even multiple datacenters in a region in a few extreme cases – has two pinch points in the network. There is the …
The NVIDIA GTC conference has a reputation for delivering announcements that reshape industry roadmaps. At this year’s event, from March 16 to 19 in downtown San Jose, the AI community will converge to explore what comes next. The marquee event remains chief executive officer Jensen Huang’s keynote at SAP Center …
This is turning into a “dog bites man” story, but the forecasts for spending in the datacenter for this year keep going up and up, and a few days ago Gartner’s economists and prognosticators finished up their tea and looked at the leaves at the bottom of a cup through …
Like Google and Meta Platforms, Amazon knows exactly how to infuse AI into its business operations such as online retail, transportation, advertising, and even the Amazon Web Services cloud. Just like Google and IBM have been their own Customer Zero for AI efforts, Amazon has been learning how to use …
Here is how we know computing could eventually be a peer to energy, transportation, sustenance, and healthcare as a basic infrastructure need – and will be a bigger part of our lives in the future, if the hyperscalers and cloud builders have their way: The front loading of enormous capital …
Pent up demand for MI308 GPUs in China, which AMD has been trying to get a license to sell since early last year, were approved so that $360 million in Instinct GPU sales that were not officially part of the pipeline made their way onto the AMD books in Q4 …
During his more than two decades with Nvidia, Rev Lebaredian has had a ringside seat to the show that has been the evolution of modern AI, from the introduction of the AlexNet deep convolutional neural network that made waves by drastically lowering the error rate at the 2012 ImageNet challenge …
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