Open-source USB tool unlocks extra AI performance on older Nvidia RTX cards

Started by BigDog10, Yesterday at 02:36 PM

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Topic: Open-source USB tool unlocks extra AI performance on older Nvidia RTX cards   Views(Read 67 times)
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BigDog10

Owners of older Nvidia graphics cards may have more AI performance available than they thought. Tom's Hardware reports on nv-uefi-unlocker, an open source tool that boots from a USB stick and removes a limit on tensor throughput on many RTX 20, 30 and 40 series cards

The tool runs before Windows or Linux loads the Nvidia driver, needs no BIOS flash or driver changes, and has to run again on every boot. It uses a community payload to unlock two speed selection registers so the card's tensor units run at full rate for FP16 and BF16 maths, which matters for AI workloads

Reported gains are large. An RTX 4060 laptop GPU went from 29.89 to 49.33 teraflops, about 1.65 times faster, and an RTX 4080 went from about 100 to 192 teraflops on BF16. An RTX 3060 12GB improved by around 1.8 times. RTX 30 and 40 series cards are listed as fully compatible, RTX 20 support is partial, and the newer RTX 50 series is not supported

There are caveats. Secure Boot must be off or configured to trust the tool, so games whose anti cheat requires Secure Boot will not work. Combining it with power limit unlocks can push cards beyond factory limits, a safety check is not built yet, and the developer of the original project does not plan to maintain a Windows version. Nvidia has not commented

This is a fascinating find for people running local AI models on consumer cards. It also raises questions about why the hardware was limited in the first place. Anyone trying it should be cautious, though, because firmware level tools carry real risks

Would you use a tool like this on your graphics card? And should Nvidia be limiting hardware people have paid for?


WWEHarry78

Turning off Secure Boot is a big trade off for gamers. Many popular competitive games now require it. This is more for AI hobbyists than players. Linux users running AI workloads benefit most
Have you tried turning it off and on again?