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atxweirdo t1_iwhowxd wrote

Reply to comment by emize in AMD Now Powers 101 of the World's Fastest Supercomputers by Avieshek

Bioinformatics and ML has taken off in recent years. Not to mention data analytics for research projects. I used to work for a supercomputer center. Lots of interesting projects were going through our queues

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paypaytr t1_iwj6zbm wrote

For ML this is useless though. They don't need supercomputers but rather cluster of well efficient GPUs

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DeadFIL t1_iwjflz1 wrote

All modern supercomputers are just massive clusters of nodes, and this list includes GPU-based supercomputers. Check out #4 on the list: Leonardo, which is basically just a cluster of ~3,500 Nvidia A100-based nodes.

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My_reddit_account_v3 t1_iwjmbs9 wrote

Ok, but why would supercomputers suck? Are they not equipped with arrays of GPUs as well?

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DeadFIL t1_iwjpc1o wrote

Supercomputers cost a lot of money and are generally funded for specific reasons. Supercomputers are generally not very general purpose, but rather particularly built to be as good as possible at one class of task. Some computers will have a lot of CPUs, some will have a lot of GPUs, some will have a lot of both, and some will have completely different types of units that are custom built for a specific task.

It all depends on the supercomputer, but some aren't designed to excel at the ML algorithms. Any of them will do wayyyy better than your home computer due to their processing power, but many will be relatively inefficient.

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My_reddit_account_v3 t1_iwjshyb wrote

Right. I guess what you are saying is you prefer to control the composition of the array of CPUs/GPUs, rather than rely on a “static” supercomputer, right?

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