Timing is a funny thing. The summer of 2006 when AMD bought GPU maker ATI Technologies for $5.6 billion and took on both Intel in CPUs and Nvidia in GPUs was the same summer when researchers first started figuring out how to offload single-precision floating point math operations from CPUs to Nvidia GPUs to try to accelerate HPC simulation and modeling workloads. …
Because they are in the front of the line for acquiring Nvidia datacenter GPUs, the hyperscalers and cloud builders are going to be the ones who benefit mightily from shortages of matrix math engines that can train AI models and run inference against them. …
If you had to sum up the second half of 2022 and the first half of 2023 from the perspective of the semiconductor industry, it would be that we made too many CPUs for PCs, smartphones, and servers and we didn’t make enough GPUs for the datacenter. …
Transitions in the datacenter take time.
It took Unix servers a decade, from 1985 through 1995, to supplant proprietary minicomputers and a lot of mainframe capacity that would have otherwise been bought. …
Heaven forbid that we take a few days of downtime. When we were not looking – and forcing ourselves to not look at any IT news because we have other things going on – that is the moment when Nvidia decides to put out a financial presentation that embeds a new product roadmap within it. …
It would be hard to find something that is growing faster than the Nvidia datacenter business, but there is one contender: OpenAI. …
In a world where Nvidia is allocating proportional shares of its GPU hotcakes to all of the OEMs and ODMs, companies like Dell, Hewlett Packard, Lenovo, and Supermicro get their shares and then they turn around and try to sell systems using them at the highest possible price. …
Not everybody can afford an Nvidia DGX AI server loaded up with the latest “Hopper” H100 GPU accelerators or even one of its many clones available from the OEMs and ODMs of the world. …
With a server recession underway and its latest Epyc CPUs and Instinct GPU accelerators still ramping, this was a predictably soft, but still not terrible in the scheme of things, quarter for AMD. …
When we think about high performance computing, it is often in the context of liquid-cooled systems deployed in facilities specifically designed to accommodate their power and thermal requirements. …
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