We don’t normally spend a lot of time writing about IBM mainframes, but these big iron systems drive a lot of transactions in the world – transactions flush with demographics and context that will feed into AI models – and will be doing native and integrated AI processing for the …
China has lots of coal but it does not have a lot of GPUs or other kinds of tensor and vector math accelerators appropriate for HPC and AI. And so as it has done with exascale-class HPC supercomputers, it is going to trade density and power efficiency for scale and …
Last year, amid all the talk of the “Blackwell” datacenter GPUs that were launched at last year’s GPU Technicval Conference, Nvidia also introduced the idea of Nvidia Inference Microservices, or NIMs, which are prepackaged enterprise-grade generative AI software stacks that companies can use as virtual copilots to add custom AI …
The semiconductor manufacturing business is absolutely immense. To give the numbers some perspective, in 2024, chip makers generated revenues that were about three quarters of the size of the US defense budget and about two-thirds the size of the social services budget allocated by Congress. And spending on chip manufacturing …
The AI boom has been very, very good to Taiwan Semiconductor Manufacturing Co, which is positioned to do well if Nvidia continues with its hegemony over AI training and inference or if the rebel alliance forms behind AMD or if the hyperscalers and cloud builders dedicate a substantial portion of …
As part of the pre-briefings ahead of the Google Cloud Next 2025 conference last week and then during the keynote address, the top brass at Google kept comparing a pod of “Ironwood” TPU v7p systems to the “El Capitan” supercomputer at Lawrence Livermore National Laboratory. And they kept doing it …
Beleaguered chip maker Intel has been looking for ways to capitalize on non-core, not large, but profitable parts of its business to raise funds for its ambitious plans to revitalize Intel Foundry and to also invest heavily in the Intel Products group. And only two weeks after taking the helm …
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PARTNER CONTENT: “Developers have to build it, right, and their first concern is to make it work,” says CentML chief executive officer Gennady Pekhimenko. “After that, when it starts to work, it’s like, ‘OK, let’s deploy it.’ And that’s where, all of a sudden, they face challenges.” Launching a new …
Making a graphics card for gamers is one thing, but manufacturing a rackscale supercomputer with over 600,000 components that burns 120 kilowatts of power, that has over 5,000 copper cables for an all-to-all interconnect mesh for 72 dual-chip compute engines, and that weighs over 3,000 pounds is another thing entirely. …
SPONSORED FEATURE: Back before there were AI factories, there were two generations of the AI Bridging Cloud Infrastructure supercomputer, built by the National Institute of Advanced Industrial Science and Technology (AIST) in Japan. AIST created what is arguably the first AI factory, merging accelerated computing platforms with cloud infrastructure software …
The HPC centers of the world like fast networks and compute, but they are also always working under budget constraints unlike their AI peers out there in the enterprise, where money seems to be unlimited to what sometimes looks like an irrationally exuberant extent. They are also don’t have a …
SPONSORED CONTENT When it comes to artificial intelligence, context is everything. The same thing holds true for human intelligence, so it stands to reason that it translates to AI since we created it in our own image. And now, we are watching companies like NVIDIA promote AI factories – literally …
If you want to be a leading in supplying AI models and AI applications, as well as AI infrastructure to run it, to the world, it is also helpful to have a business that needs a lot of AI that can underwrite the development of homegrown infrastructure that can be …
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 …
It is funny how companies can find money – lots of money – when they think IT infrastructure spending can save them money, make them money, or do both at the same time. This is the hope with AI, and everyone is trying to benefit from it in those ways. …
Spending on AI systems in 2024 just utterly blew by the expectations of the major market researchers and those who dabble in metrics like we do. There has just been an unprecedented amount of spending, mostly for systems that are accelerated by Nvidia GPUs. It remains to be seen how …
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