If high bandwidth memory was widely available and we had cheap and reliable fusion power, there never would have been a move to use GPU and other compute engines as vector and matrix math offload engines. …
Finding new functional materials for batteries and catalysts and lots of other uses is a major goal of researchers around the world. …
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. …
Spoiler alert!
A lot of neat things have just been added to the Arm Neoverse datacenter compute roadmap, but one of them is not a datacenter-class, discrete GPU accelerator. …
Without question, the biggest bottleneck in artificial intelligence and for a lot of HPC workloads today is bandwidth. …
With each successive Intel Xeon SP server processor launch, we can’t help but think the same thing: it would have been better for Intel and customers alike if this chip was out the door a year ago, or two years ago, as must have been planned. …
The most exciting thing about the Top500 rankings of supercomputers that come out each June and November is not who is on the top of the list. …
There is little question that generative AI as well as other kinds of machine learning are going to augment applications in every industry and in every part of the application stack in the coming years. …
Some details are emerging on Europe’s first exascale system, codenamed “Jupiter” and to be installed at the Jülich Supercomputing Center in Germany in 2024. …
Other than Hewlett Packard Enterprise, who wants to build the future NERSC-10 supercomputer at Lawrence Berkeley National Laboratory or the future OLCF-6 system at Oak Ridge National Laboratory? …
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