The Buck Still Stops Here For GPU Compute
It has taken untold thousands of people to make machine learning, and specifically the deep learning variety, the most viable form of artificial intelligence. …
It has taken untold thousands of people to make machine learning, and specifically the deep learning variety, the most viable form of artificial intelligence. …
Paid Feature Few organizations have the resources and talent on hand to skillfully navigate HPC infrastructure management and the emerging demands of AI/ML training and inference simultaneously. …
Hewlett Packard Enterprise was a bit ahead of the curve when it announced in 2019 that by this year it would be offering its entire product portfolio as a service and that its GreenLake hybrid cloud platform would be the foundation of the effort. …
When the “Aldebaran” datacenter GPUs were launched by AMD last November for the HPC and AI crowd pushing up into the exascale stratosphere, only the two top-end models of the Instinct GPU accelerators –ones that use the Open Accelerator Module (OAM) form factor put forth by Facebook and Microsoft under the Open Compute Project – were actually available. …
Last fall ahead of the SC21 supercomputing conference, AMD said it was going to be the first of the major compute engine makers to add 3D vertical L3 cache to its chips, in this case to variants of the “Milan” Epyc 7003 series of processors that debuted in March 2021 called the “Milan-X” chips. …
To hardware or not to hardware, that is a real question for vendors peddling all kinds of software in the datacenter. …
The Slurm Workload Manager that has its origins at Lawrence Livermore National Laboratory as the Simple Linux Utility for Resource Management – and which is used on about two-thirds of the most powerful HPC systems in the world – is looking for new jobs to take on across hybrid cloud infrastructure and machine learning systems running at scale. …
When any new abstraction layer comes to compute, it can only think in integers at first, and then it learns to do fractions and finally, if we are lucky – and we are not always lucky – that abstraction layer learns to do multiplication and scale out across multiple nodes as well as scaling in – slicing itself into pieces – within a single node. …
Over the past decade, much of the focus with machine learning has been on CPUs and accelerators, primarily GPUs but also custom ASICs, with advances in the chip architecture aimed at boosting parallel math performance. …
Some of the most important luminaries in the HPC sector have spoken from on high, and their conclusions about the future of the HPC market are probably going to shock a lot of people. …
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