The article discusses the rise of AI and its impact on the traditional HPC community. It explores the challenges of obtaining datacenter-class GPUs and the potential benefits of hybrid AI-HPC systems. The author also interviews Scott Tease, general manager of HPC and AI at Lenovo, to discuss the divergence of AI and HPC architectures and its implications for the simulation and modeling market.
If you are in the traditional HPC community, it is not hard to be of two minds about the rise of AI and the mainstreaming of generative AI. At the very least, the GenAI tsunami makes it easier to argue for hardware budgets even though it is extremely difficult to get your hands on any datacenter-class GPU these days.
And because of this, organizations that are buying hybrid AI-HPC systems are going to be able to do more HPC processing as their systems get upgraded to do more AI – at least in theory. It is good – and fun – to talk about theory, but eventually you need to get grounded in some reality. And that is why we like to touch based with Scott Tease, general manager of HPC and AI at Lenovo, around the same time that the SC supercomputing conference takes place each year. We did so in the wake of the SC23 event, and among other things, wanted to find out if AI and HPC architectures are diverging and what this might mean for the traditional HPC simulation and modeling market.I don’t know about you, but I am sick of hearing about AI as if it is the only important kind of HP
AI HPC Generative AI Datacenter-Class GPU Hybrid AI-HPC Systems Simulation Modeling
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