Timothy Prickett Morgan

Sponsored Feature Arm is starting to fulfill its promise of transforming the nature of compute in the datacenter, and it is getting some big help from

COMMISSIONED As the AI era unfolds, I have been reflecting on my journey in the tech industry. What’s happening with AI at the edge right now reminds me

Anyone who thinks that Intel is easy to kill need look no further than the historical trends of the Mercury Research market share statistics that we see each quarter. Data for the third quarter of 2024 was just announced, and we have paired this with historical trends in shipments and revenues from Gartner to give you a sense of what the heck is going on with X86 CPUs in the datacenter.

We commented back in August when the Hot Chips 2024 conference was underway at Stanford University that it was odd that IBM did reveal some of the speeds and feeds of the Power11 processor that we all know is coming in 2025. And when the TechXchange 2024 partner event was held in Las Vegas a few weeks ago, we were pretty sure that IBM was working on some sort of accelerated system for GenAI applications and a week later we remembered that the obvious pairing was a Power System host with scads of IBM’s own “Spyre” AI accelerators running WatsonX models or other open source ones like the Llama family from Meta Platforms.

Lawrence Livermore National Laboratory, Sandia National Laboratories, and Los Alamos National Laboratory are known by the shorthand “Tri-Labs” in the HPC community, but these HPC centers perhaps could be called “Try-Labs” because they historically have tried just about any new architecture to see what promise it might hold in advancing the missions of the US Department of Energy.

There has been a lot more churn on the November Top500 supercomputer rankings that is the talk of the SC24 conference in Atlanta this week than there was

Every couple of years, Lawrence Livermore National Laboratory gets to install the world’s fastest supercomputer. And thankfully the HPC center usually chooses a machine that not only fulfills its mission of managing the nuclear weapons stockpile of the United States military, but also picks a mix of technologies that advances the state of the art in supercomputer.

We have said it before, and we will say it again as everyone is chewing on the financial results that Nvidia just turned in for its third quarter of fiscal 2025 ended in October. Nvidia does not have to be in any hurry to deliver its “Blackwell” GPU platforms, which are rumored to be having a new set of delays, because companies will still be eager to pay for platforms based on the prior generation of “Hopper” GPUs. It takes a little more than twice as many Hopper GPUs to do the work of a Blackwell GPU, but the Blackwell GPU only drives around 1.7X more revenue and is, by virtue of its advanced manufacturing, probably more costly to create.

COMMISSIONED What’s holding back the next big breakthrough in AI – processing power or the infrastructure supporting it? The short answer is: Both. But

Intel was the first of the major CPU makers to add HBM stacked DRAM memory to a CPU package, with the “Sapphire Rapids” Max Series Xeon 5 processors, but with the “Granite Rapids” Xeon 6, Intel abandoned the use of HBM memory in favor of what it would hope would be more main stream MCR DDR5 main memory, which has multiplexed ranks to boost bandwidth by nearly 2X over regular DDR5 memory.