The cluster architectures for AI training and inference are driving unprecedented growth in the datacenter infrastructure spending, but they are also having a reflective and beneficial impact on HPC architectures thanks to the relative ease with which one can get funding for AI initiatives and the need to upgrade existing …
Here’s a riddle for you: What’s the difference between an economic bubble and an economic transformation? I don’t know, but if either pops, a bunch of economists are gonna lose their jobs. And if the GenAI bubble keeps on embiggening or the GenAI transformation keeps on expandening, a whole lot …
PARTNER CONTENT We are entering a new era where AI isn’t just a tool for transformation but the foundation for reinvention. Frontier firms aren’t waiting. Already, they’re architecting the future with agentic systems, intelligent infrastructure, responsible practices, and resilient data platforms, compounding their competitive advantage. What took months to prototype …
SPONSORED POST Hewlett Packard Enterprise sets out its latest advances in large-scale computing at the SC25 high performance computing conference in November. In recent weeks, it has confirmed two new systems for the Oak Ridge National Laboratory in the US in collaboration with AMD. The Discovery exascale machine and the …
Nvidia has spent much of the year launching new products and partnerships that aim to ensure it keeps its place atop the wild west that is still the AI market while establishing its place in the emerging quantum computing space, where co-founder and chief executive officer Jensen Huang sees Nvidia …
For the past two years now, we have been picking apart the semi-annual rankings of supercomputers known as the Top500 is a different way, focusing on the new machines that come into each list in either June or November. This, we thinks, gives us a sense of what people are …
There is a vicious cycle that comes from screwing up, but there is also a virtuous cycle that comes from digging yourself out of the hole and not only not screwing up anymore, but catching up to and then leapfrogging the competition through good engineering, hard work, and a little …
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Space has always been a premium in the datacenter, but the heat is on – quite literally – to drive up the density of GPU and XPU compute not just because real estate is expensive, but because latency is perhaps more expensive. The closer you can get compute engines and …
Quantum computing is finally heating up. There is a heady mix of high-profile and highly resourced big tech players like Google, Microsoft, Amazon Web Services, and Nvidia either building QPUs, simulating them, or integrating them with classical supercomputers in addition to well-funded younger companies and startups, such as QuEra, IonQ, …
There are somewhere on the order of 50,000 reasonably large companies, academic centers, and governments in the world that the enterprise IT market is like the ocean on a calm day in the doldrums. While there may be lots of little whirlpools and a bunch of choppiness, it is all …
Over the past decade, it has been interesting to watch companies push the rock that is quantum computing up the steep hill. As Yuval Boger, chief commercial officer for QuEra told us this summer, it was only five or six years ago that people were still asking if building a …
If there is one thing that the AI model builders and the neoclouds both agree on, it is that they do not want to worry about storage. The hyperscalers and cloud builders have created their own disparate kinds of storage over the decades and think they already know everything. They …
There are two competing forces in IT, and they are at play during the GenAI era as much as they have ever been during prior eras in the datacenter. One is the desire to provide a completely integrated system, ready for applications, from a single supplier. The other is to …
If all goes according to the high end of plan, then AMD should kiss $10 billion in revenues in the fourth quarter of this year, and if it was low-balling that number a little, then it should break through $10 billion and put the wrap on a $34.3 billion year …
Chip designs are busting out beyond the reticle limits of lithography machines, making chiplets and high-bandwidth, in-package die-to-die interconnects inevitable. And AI training workloads are busting through datacenter walls, making scale out networks to lash together datacenters or even multiple regions into a single, logical datacenter just as inevitable. Given …
Here is a question for you. What is more difficult: predicting the weather thirty days out or what global AI infrastructure spending will be out to the end of the decade? We don’t know, but it sure looks like someone is gonna spend a lot of money on infrastructure either …
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