GPU Unlock解锁RTX张量核心限制
Zagitta主导的GPU Unlock等社区项目通过修改GPU启动配置，解除部分NVIDIA GeForce RTX 20、30、40系列显卡在FP32累加的FP16/BF16 Tensor Core运算中的指令发射率限制。Tom’s Hardware和36氪 AI汇总的测试显示，部分矩阵运算峰值吞吐接近翻倍，Ampere显卡的LLM预填充提升14%至36%，但解码和INT8性能基本不变。Linux方案已有公开实现，Windows支持及具体卡型覆盖仍处于实验或未完成状态。
这些项目可能让部分本地AI和图像生成用户从现有RTX硬件中获得更多算力，但实测收益取决于显卡与负载，不能据此认定LLM解码或游戏性能会同步提升。
Basically saw on twitter claims that 3090 has half of the cuda kernels disabled:
My 3090s just got 1.9x FASTER at BF16 tensor math!!! Same cards, same driver, same 300W, one Linux kernel module.
bf16 tensor pipe: 82 -> 155 TFLOPS cuBLAS BF16 GEMM 8192: 64 -> 99 TFLOPS TF32: 41 -> 79 TFLOPS
NVIDIA ships every 3090 with fp32-accumulate tensor math at half speed. The driver even reports it: FMLA32 = 1/2. gpu-unlock by Zagitta sets it to full before the NVIDIA driver loads. After a cold boot all 4 of my cards say FMLA32 = full.
Real inference got less than I predicted. Strata, Qwen3.8 Flash-Next on 2 cards, prefill: 4K: +12% 10K: +12% 90K: 3205 -> 3536 tok/s, +10%
Before installing I said +14 to 19% at 90K, so I was wrong. The GEMM phases got 23% shorter, but they are only about 40% of Strata prefill, and the int8 experts, copies and CUDA core kernels didnt get any faster.
Outputs did not change. With the same expert cache size, my log-prob dump over 1996 teacher-forced positions is the same file byte for byte as the stock run before the module.
Wondering if it will work for 40 series cards
submitted by /u/UltramanQuar [link] [comments]
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