The history of computing teaches us that software always and necessarily lags hardware, and unfortunately that lag can stretch for many years when it comes to wringing the best performance out of iron by tweaking algorithms. …
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. …
UPDATED: It is funny what courses were the most fun and most useful when we look back at college. …
The National Center for Supercomputing Applications at the University of Illinois just fired up its Delta system back in April 2022, and now it has just been given $10 million by the National Science Foundation to expand that machine with an AI partition, called DeltaAI appropriately enough, that is based on Nvidia’s “Hopper” H100 GPU accelerators. …
A year ago, at its Google I/O 2022 event, Google revealed to the world that it had eight pods of TPUv4 accelerators, with a combined 32,768 of its fourth generation, homegrown matrix math accelerators, running in a machine learning hub located in its Mayes County, Oklahoma datacenter. …
UPDATED Like many HPC and AI system builders, we are impatient to see what the “Antares” Instinct MI300A hybrid CPU-GPU system on chip from AMD might look like in terms of performance and price. …
The tech world is awash with generative AI, which for a company like Nvidia, is a good thing. …
In the absence of hard numbers, we have never been shy about making estimates because educated guesses is all you sometimes have to make a decision or to derive some kind of insight. …
Last May, after we had done a deep dive on the “Hopper” H100 GPU accelerator architecture and as we were trying to reckon what Nvidia could charge for the PCI-Express and SXM5 variants of the GH100, we said that Nvidia needed to launch a Hopper-Hopper superchip. …
GPU computing platform maker Nvidia announced its financial results for its fiscal fourth quarter ended in January, which showed the same digestion of already acquired capacity by the hyperscalers and cloud builders and the same hesitation to spend by enterprises that other compute engine makers for datacenter computing are also seeing. …
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