sudo apt --purge remove "*cuda*" "*cublas*" "*cufft*" "*cufile*" "*curand*" "*cusolver*" "*cusparse*" "*gds-tools*" "*npp*" "*nvjpeg*" "nsight*" "*nvvm*" sudo rm -rf /usr/local/cuda*
isn't a "revolutionary" jump like the move from 11 to 12, but it is a necessary upgrade for anyone moving toward Blackwell hardware or looking to shave seconds off their AI model initialization times. For researchers and enterprise developers, the stability and refined JIT optimizations make it the most polished version of the 12-series to date. Pros: Essential for Blackwell and Grace Hopper hardware. cuda toolkit 126
Careful upgrades typically yield performance and maintenance benefits without major rewrites. Here is the status of CUDA 12
Modern data scientists rarely write raw CUDA kernels. Instead, they rely on frameworks. Here is the status of CUDA 12.6 support as of Q4 2024: they rely on frameworks.
| GPU | -arch value | |----------------|---------------| | A100 | sm_80 | | RTX 3090/4090 | sm_86 / sm_89 | | H100 | sm_90 | | L4 / L40 | sm_89 | | GTX 1080 Ti | sm_61 |