Measuring the GPU/CPU tradeoff

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2024-12-27 12:30:08

There's a lot of well-deserved excitement around graphics processing units (GPU), not just in the stock market but the software world too. The success stories are too good to ignore. I've heard GPUs described as an "accelerant", and one might get the impression that sprinkling a little GPU on a project will be magic pixie dust to make it go faster. It's also likely to explode if you're not careful.

There are obvious and impressive applications in graphics, gaming, simulation, statistics, deep learning - any field that requires heavy number crunching with linear algebra routines. And these are many of the hottest fields in computing at the moment for a reason.

But there is a downside for software developers. In order to see any benefit at all from a GPU and to avoid wasting time, energy and money, you need to keep the hardware busy with large yet simple math problems.

Not all software is amenable to this style of programming. If not, the humble and ubiquitous CPU outperforms the GPU in many meaningful ways. But how do you know?

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