It is beginning to look like the Dell Technologies and Hewlett Packard Enterprose, the world’s two biggest original equipment manufacturers, are finally going to start benefitting from the generative AI wave, mainly because they are finally getting enough allocations of GPUs from Nvidia and AMD that they can start addressing the needs of customers who don’t happen to be among the hyperscalers and largest cloud builders. …
It looks like Hewlett Packard Enterprise might be having a datacenter networking revival. …
The ProLiant server business is down in the dumps, and the storage business is in a slump. …
It was a fortuitous coincidence that Nvidia was already working on massively parallel GPU compute engines for doing calculations in HPC simulations and models when the machine learning tipping point happened, and similarly, it was fortunate for InfiniBand that it had the advantage of high bandwidth, low latency, and remote direct memory access across GPUs at that same moment. …
There is perhaps no better logo for Hewlett Packard Enterprise than the box. …
The IT industry, like every other industry we suppose, is in a constant state of dealing with the next bottleneck. …
In March 2020, when Lawrence Livermore National Laboratory announced the exascale “El Capitan” supercomputer contract had been awarded to system builder Hewlett Packard Enterprise, which was also kicking in its “Rosetta” Slingshot 11 interconnect and which was tapping future CPU and GPU compute engines from AMD, the HPC center was very clear that it would be using off-the-shelf, commodity parts from AMD, not custom compute engines. …
Any time you build anything with more than 60 million parts, it is going to be a headache. …
Significant business and architectural changes can happen with 10X improvements, but the real milestones upon which we measure progress in computer science, whether it is for compute, storage, or networking, come at the 1,000X transitions. …
When it comes to supercomputing in academia, the cost of a cluster is almost always an issue and this, coupled with the desire to drive as much compute as possible, drives architectural choices. …
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