Comments (2)
It depends on what you would like to do and which hardware you own.
Compiling with MKL was actually always slower for me than native.
The best solution would be to provide both options.
from batchglm.
This also did not seem much faster on my machine, let's watch this space.
from batchglm.
Related Issues (20)
- 'Simulator' object has no attribute 'np_clip_param' when following diffxpy tutorial HOT 2
- [TF2] Do we need float64? HOT 5
- Controlling verbosity with an argument and proper logging HOT 1
- expand dims bug with da.test.wald HOT 1
- print(test.model) throws RecursionError HOT 2
- tests: cannot import name 'Simulator' from 'batchglm.api.models' HOT 4
- Make Unit Tests Work
- Model Status Tracker
- multi-dispatch for `init_par`
- Nicer model initialisation HOT 2
- [python 3.10] add switch case
- Move `InputDataGLM` to a static util
- Document what `ModelContainer` does
- Check that get_model_container() works with diffxpy interface
- Stop using multiprocessing for fitting dispersion models earlier HOT 1
- Error when batch_size[1] <= number of genes HOT 2
- New Release Issues
- Make `init_par` a class Method HOT 1
- Investigate Removing `.params`
- Not compatible with Python 3.10 HOT 2
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from batchglm.