Time is money when it comes to generative AI, as is the case with most technologies. But with generative AI, it is big money. And the longer it takes for an AI model to do anything, such as training on data or generating images and video, the more money is …
Finding new functional materials for batteries and catalysts and lots of other uses is a major goal of researchers around the world. And the design and discovery of new materials often requires computer simulations running on the world’s fastest supercomputers using specialized software that can determine properties at the quantum …
At his company’s GTC 2024 Technical Conference this week, Nvidia co-founder and chief executive officer Jensen Huang, unveiled the chip maker’s massive Blackwell GPUs and accompanying NVLink networking systems, promising a future where hyperscale cloud providers, HPC centers, and other organizations of size and means can meet the rapidly increasing …
Last November, we got a sneak peak at a supercomputer called “Ceiba” that would be built jointly by Nvidia and Amazon Web Services, based on its then-new GH200 Grace-Hopper CPU-GPU compute complexes, its NVLink Switch 3 memory fabric for GPUs, and the Elastic Fabric Adapter (EFA2) Ethernet interconnect that is …
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. Some historical context is warranted to put the Blackwell …
If you want to take on Nvidia on its home turf of AI processing, then you had better bring more than your A game. You better bring your A++ game, several vaults of money, and a few bags of good luck. Maybe a genie in a bottle would help, too. …
It is a pity that we can’t make silicon wafers any larger than 300 millimeters in diameter. If there were 450 millimeter diameter silicon wafers, as we were promised so long ago, this being Pi Day and all, then Cerebras Systems would have been able to get a 2.25X performance …
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If you handle hundreds of trillions of AI model executions per day, and are going to change that by one or two orders of magnitude as GenAI goes mainstream, you are going to need GPUs. Lots of GPUs. And apparently Meta Platforms does, and it is getting out its big, …
Ultimately, every problem in the constantly evolving IT software stack becomes a database problem, which is why there are 418 different databases and datastores in the DB Engines rankings and there are really only a handful of commercially viable operating systems. But what if the operating system is the problem? …
With the reticle limit for chip manufacturing pretty much set in stone (pun intended) at 26 millimeters by 33 millimeters down to 2 nanometer transistor sizes with extreme ultraviolet lithography techniques and being cut in half to 26 millimeters by 16.5 millimeters for the High-NA extreme ultraviolet lithography needed to …
As we have noted before, vector databases aren’t new even though people talk about them that way, and in fact can trace their origins back a few decades. Exactly when depends on who you ask, but their popularity began to ramp along with machine learning technologies over the past 10 …
The edge is continuing to become a place where IT infrastructure vendors need to be, and that includes chip makers, all of whom have strategies to push their silicon to where the data is increasingly being generated and needs to be stored, processed, and analyzed. AMD, armed with the technology …
Things would go a whole lot better for server designs if we had a two year or better still a four year moratorium on adding faster compute engines to machines. That way, we could let memory subsystems and I/O subsystems catch up and get better utilization of those compute engines …
Note: This story augments and corrects information that originally appeared in Half Eos’d: Even Nvidia Can’t Get Enough H100s For Its Supercomputers, which was published on February 15. So, as it turns out, there are two supercomputers named Eos, and even the people in the press relations department at Nvidia, …
By the time that the founders of Achronix, who were all techies from Cornell University, decided to found their own FPGA company twenty years ago, FPGAs had already been in the field for twenty years and the market was dominated by Xilinx (now part of AMD) and Altera (still part …
It is a strange time in the generative AI revolution, with things changing on so many vectors so quickly it is hard to figure out what all of this hardware and software and people-hours costs and what it might be worth when it comes to transforming, well, just about everything. …
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