Sponsored Feature: It’s a decade and a half since researchers dazzled the tech world by demonstrating that GPUs could be used to dramatically accelerate key AI operations. …
It is very rare for any of the major semiconductor suppliers of the world to ever admit that things are going wrong, even when we all know that they have been. …
If there is one thing that is consistently true about HPC clusters for the past thirty years and for AI training systems for the past decade, it is as workloads grow, the network becomes increasingly important – and perhaps as important as packing as much flops in a node as physically and thermally makes sense. …
If the semiconductor business teaches us anything, it is that volumes matter more than architecture. …
The old AMD – the one before Lisa Su took over – was often brilliant with its instruction set architecture and CPU designs, but sometimes perplexingly careless with its design choices and chip roadmaps. …
Like everyone else on planet Earth, we were expecting for the next generation of graphics cards based on the “Ada Lovelace” architecture to be announced at the GTC fall 2022 conference this week, but we did not expect for the company to deliver a passively cooled, datacenter server friendly variant of the GeForce RTX 6000 series quite so fast. …
You can’t be certain about a lot of things in the world these days, but one thing you can count on is the voracious appetite for parallel compute, high bandwidth memory, and high bandwidth networking for AI training workloads. …
China is the world’s second largest economy, it has the world’s largest population, and it is only a matter of time before has a world-class technology ecosystem spanning the smallest transistors to the largest hyperscale and HPC systems. …
It was absolutely inevitable that China would try to create its own GPU compute engines. …
We have been talking about silicon photonics so long that we are, probably like many of you, frustrated that it already is not ubiquitous. …
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