NVIDIA’s aging GeForce RTX 30 Series (codename Ampere) GPUs apparently have a considerable amount of untapped computing potential. A new open-source project called GPU Unlock, developed by GitHub user Zagitta, allows Ampere GPUs to overcome certain artificial performance restrictions, nearly doubling their Tensor Core compute throughput in specific workloads without requiring a modified NVIDIA driver or a permanent VBIOS flash. The project specifically targets the instruction issue-rate limitation affecting FP16/BF16 Tensor Core operations with FP32 accumulation, which operates at a reduced rate on consumer Ampere graphics cards compared to their professional counterparts. By removing this restriction, the tool effectively enables […]
Read full article at https://wccftech.com/nvidia-geforce-rtx-30-gpus-get-up-to-2x-faster-ai-compute-performance-with-new-gpu-unlock-mod-real-world-gains-of-up-to-60/