PtyPy 0.8 release notes
We're excited to bring you a new release, with new engines, CuPy support and other improvements. The docs aren't yet up to date with this one unfortunately but we are working on it.
GPU acceleration
An alternative CUDA implementation based on cupy
has been implemented, providing the same feature as the PyCuda
based engine.
It can be imported using
import ptypy
ptypy.load_gpu_engines('cupy')
which will load engines such as DM_cupy
, RAAR_cupy
, ML_cupy
, EPIE_cupy
and SDR_cupy
.
Engine updates
- New WASP algorithm including GPU acceleration, available as custom engines by importing the module from
ptypy.custom
(thanks to Timothy Poon) - Experimental implementation of the ThreePIE algorithm (multislice) which is available as custom engine by importing the module
ptypy.custom.threepIE
and using the engine asThreePIE
(thanks to Yiran Lu and Maik Kahnt) - We provide templates for both algorithms, we are working on additional documentation
Additional build changes
- Added Euclidean noise model to core ML engine (thanks to Jari Fowkes)
- New saving mode "used_params" that will save parameters used during reconstruction into the output .ptyr file
- Introducing core functions
copy_state
andrestore_data
which allow for more efficient parameter sweeps
Breaking change
Removed NCCL support from pycuda engines to avoid dependency on CuPy. The new CuPy engines have been implemented with NCCL support.
Contributors
- Benedikt Daurer
- Timothy Poon
- Joerg Lotze
- Bjoern Enders
- Maik Kahnt
- Yiran Lu
- Jari Fowkes