Comments (2)
jonpvandermause
commented on July 20, 2024
@YuuuuXie @nw13slx Is there still a parallelization bug? I remember noticing an issue with the parallelization in otf a few months ago, but patched it with 5dd377a and haven't noticed any problems since. Seems that the parallel methods as implemented work fine and give a significant speed up.
But yes, the predict on structure methods can be moved, perhaps changed to methods of the gp class.
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stevetorr
commented on July 20, 2024
To do: Test an OTF job on Odyssey to ensure this works in parallel. Test if moving it to another file breaks anything (moving it outside of a class seems to make it work okay, says Yu).
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Related Issues (20)
- Compiling LAMMPS with KOKKOS Library Failing with FLARE HOT 6
- MemoryError calling GaussianProcess HOT 1
- Wrong `QE` DFT calculator name in GoogleColab tutorial? HOT 2
- Building with classic intel compilers fails: null pointer
- Coogle colab tutorial is missing HOT 2
- Time of Update GP (s) increases a lot as more DFT calls HOT 1
- otf run hangs at the very first step
- Trajectory extraction HOT 7
- OTF SGP models with force_only=True, not working with OTF.from_checkpint() HOT 2
- Output file inquire HOT 3
- Is the specific coarse-grain version available？ HOT 1
- seg fault when predicting local uncertainty with trained sgp calculator HOT 4
- Potential Parallelism for Hyperparameter Tuning
- Execluding some species from training HOT 1
- Bug: Python API cannot save trained model (Segmentation fault, list index out of range) HOT 3
- Adding 'Select' atomic environments to a pre-trained SGP Model using off-line training HOT 3
- Can't clone flare on windows because of tests/test_files/output_files/. Possibly OUTCAR naming not allowed on windows HOT 1
- Google Colab FLARE+LAMMPS crashing HOT 3
- About Mapped GP HOT 1
- Mapped Model in LAMMPS inaccurate compared to ASE SGP Model HOT 4
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