GPU-unlock: FP/BF16 instruction issue rate on Nvidia 3000's cards

GPU unlock 1.0.0 Unlock FP/BF16 instruction issue rate on Nvidia 3000's cards to their professional equivalents This Linux kernel module combines the CMP unlocker's V67/PLM technique with the pre-driver timing of the UEFI approach. It runs the unlock, writes the speed selectors (SS0 0x88888888, which selects the full BF16 rate, and the 4-bit SS1 0x8 IMLA4) and performs FLR before the unmodified NVIDIA driver binds the card. It is neither a UEFI application nor a patched NVIDIA driver. The benefit of this early kmod driver is that it does not require manual patching each time nvidia releases a new driver version. The effect of this unlock is that it doubles the instruction issuing speed of FP/BF16 FMA into FP32 operations on GA102, GA103, GA104 and GA106 cards. 3090 Ti dense 8192³ GEMM at 450 W, five-sample medians with FP32 accumulation: Input Before After FP16 87.46 TFLOPS 118.39 TFLOPS BF16 87.50 TFLOPS 157.41 TFLOPS TF32 42.58 TFLOPS 82.61 TFLOPS Tested cards Results reported by users. The module accepts every GeForce ID listed in kernel/gpu_unlock/main.c, but the cards below are the ones someone has reported on. Please add yours with a compatibility report, whether it worked or not. Chip Card PCI ID Result BF16 GEMM gain Reports GA102 RTX 3090 Ti 10de:2203 Unlocked +68–80% #1 GA102 RTX 3090 10de:2204 Unlocked +25–67% #5, #9, #10, #17, #25, #27, #33 GA102 RTX 3080 Ti 20 GB (OEM, GA102-250) 10de:2205 Unlock completes, BF16 stays at half rate — #28 GA102 RTX 3080 10 GB 10de:2206 Unlocked +70–73% #14 GA102 RTX 3080 20 GB (memory upgrade) 10de:2206 Unlocked +56–59% #10, #15 GA104 RTX 3070 10de:2484 Unlocked +73–81% #10, #12 GA104 RTX 3070 Ti 10de:2482 Not tested with this module (the same unlock worked from a UEFI port on Windows) — #32 GA106 RTX 3060 12 GB 10de:2504 Unlocked about +80% #13, #31 GA103 any 10de:2414 No reports yet — — The gains are dense GEMM throughput from each report's own benchmark, so they are not directly comparable. The power limit matters a lot: the lowest figure (+25%) is from cards capped at 225 W. Matrix-heavy work speeds up: LLM prefill (+14–36% in #9, #15, #25 and #33), diffusion and FlashAttention. LLM decode, which is limited by memory bandwidth, and INT8 work stay about the same. The reports that compared outputs found them bit-identical before and after. Reports also cover up to four cards in one machine, the card driving the display, and cards passed through to a VM with vfio-pci (#17). How to install First run: git clone …