In March, Nvidia introduced its GH100, the first GPU based on the new “Hopper” architecture, which is aimed at both HPC and AI workloads, and importantly for the latter, supports an eight-bit FP8 floating point processing format. …
As is well known, we like feed and speeds and slots and watts metrics here at The Next Platform for any kind of gear that runs in the datacenter. …
Et tu, Meta?
Of all of the world’s hyperscalers and large cloud builders, only Meta Platforms, dominated by its Facebook and related social network businesses like Instagram and WhatsApp, is a pure-play hyperscaler. …
With each passing generation of GPU accelerator engines from Nvidia, machine learning drives more and more of the architectural choices and changes and traditional HPC simulation and modeling drives less and less. …
Within a year or so, with the launch of the “Grace” Arm server CPUs, it will not be heresy for anyone at Nvidia to believe, or to say out loud, that not every workload in the datacenter needs to have GPU acceleration. …
The 3D stacking of chips has been the subject of much speculation and innovation in the past decade, and we will be the first to admit that we have been mostly thinking about this as a way to cram more capacity into a given compute engine while at the same time getting components closer together along the Z axis and not just working in 2D anymore down on the X and Y axes. …
It is always an exciting time when there is a new compute engine coming into the market, and interest is particularly keen with any new Arm server chip entry. …
Software maker VMware has always been about tight partnerships with other tech vendors. …
When the top brass at Intel say that the “Sapphire Rapids” Xeon SP CPUs and “Ponte Vecchio” Xe HPC GPUs that are coming out early next year represent the “largest architectural shift in over a decade,” they ain’t kidding. …
As Google’s batch sizes for AI training continue to skyrocket, with some batch sizes ranging from over 100k to one million, the company’s research arm is looking at ways to improve everything from efficiency, scalability, and even privacy for those whose data is used in large-scale training runs. …
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