yoad.tewel:

any performence difference between cuda 11.0 and 11.1 (both using cudnn 8.0.5), with rtx 3070?


Not as of now, since most (if not all) native PyTorch kernels are memory bandwidth bound and wouldn’t benefit from an increase in compute performance, while future cudnn and cublas versions should ship with sm86-specific instructions to increase the performance on the 30xx series.



 yoad.tewel:

difference between performence of pytorch nightly and pytorch 1.7.1 right now reagarding rtx 3070?


The nightly release gets the latest updates, e.g. such as the usage of fastAtomicAdd for trilinear upsampling 7, and could thus improve the performance.
However, while I don’t have a bad experience with the stability of the nightly binaries, you might want/need to stick to the stable release.