After focusing on CPUs only, it’s time to turn up the performance and discuss graphics card folding. Today’s graphics cards are massively parallel, and lend themselves to molecular dynamics problems more so than general CPUs. Folding@home has benefited from developing projects to run on graphics cards. Gamers, naturally competitive creatures by nature, have taken the F@H stats by storm. Except for a few incredibly complex multi-CPU systems, high-end folding rigs are almost entirely GPU based at this point in time.
GPUs offer increased performance and efficiency compared to CPUs. In order to offer a fair comparison to the CPU hardware tested on this blog (all very old by 2017 standards), I loaded up F@H on my 5-year-old Sapphire RADEON HD 7970 to see how it compares to the elderly hardware I’ve tested so far. The results speak for themselves (production plot courtesy of http://folding.extremeoverclocking.com/)
I ran F@H for multiple days in order to get some good averaging on the results. As you can see from the production graph, some projects return more points than others, but at an average PPD of nearly 150K, the Radeon 7970 destroys the CPU-based competition. More importantly, it does so with much more efficiency than processors.
Performance Summary: GPU vs CPU
Efficiency Summary: GPU vs CPU
Even though more total power was consumed, running Folding@home on a high-end graphics card results in much more science for a given amount of power. Next time, we’ll put a modern mid-range graphics card to the test to see how far things have come in the past 5 years…
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