Hi @matt1 , as the code for low-memory mode is essentially the same as the previous NU-refine we would not expect to see a much larger use of VRAM if all the other refinement settings are the same. Were you previously running the same settings for local, global refinement and per particle scale for successful runs in the previous version of cryoSPARC?
I have tested a box of 650 on a card with ~11GB in low-memory mode with and without without CTF refinement and NU refine was able to complete. Local refinement in particular can use quite a lot of VRAM with the default settings, so would you mind testing the following to find which step is problematic for your data:
A. NU refine with low memory mode, and with GPU batch size of images to 200 for local refinement
If this still crashes, could you please try and split the process up into the steps below:
- NU-refine run in low-memory mode without local and global CTF refinement
- Global CTF refinement
- Local CTF refinement with GPU batch size of images: 200
- Homogeneous reconstruct
With the new code (not low memory mode), the speed of NU-refine has been accelerated by keeping the maps in GPU memory, so we do expect this to require more VRAM than previously, as explained in this post.