heat
heat copied to clipboard
Distributed tensors and Machine Learning framework with GPU and MPI acceleration in Python
**Feature functionality** Will result in significant performance enhancement. Probably requires expanding the tests.
**Feature functionality** Will result in significant performance enhancement. Probably requires expanding the tests.
In PR #1228 (issue #1184) we introduce in-place versions for functions in `heat/core/arithmetics.py`. There are more functions that have in-place versions in PyTorch which we could integrate in Heat (e.g....
**Related** #1242 #1186 **Feature functionality** Provide a summary page with internal functions, `DNDarray` attributes and methods that make life easier when developing new features. **Additional context** Potential starting point: https://github.com/helmholtz-analytics/heat/pull/1216/files#r1368091192...
**Feature functionality** computes the cholesky decomposition Intended scope: - real/complex matrices - `split` $\in${ `0,1,None`} - of course, appropriate scalability of the routine is desired **Additional context** https://numpy.org/doc/stable/reference/generated/numpy.linalg.cholesky.html https://pytorch.org/docs/stable/generated/torch.linalg.cholesky.html https://data-apis.org/array-api/latest/extensions/linear_algebra_functions.html?#linalg-cholesky-x-upper-false...
1. When testing the current implementation of `heat.meshgrid`, PyTorch throws the following warning ``` UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. ```...
**Related** #1186 **Feature functionality** At this time our infos on the GitHub repo, esp. onboarding and contributing instructions, have diverged from the [ReadTheDocs docs](https://heat.readthedocs.io/en/latest/) We need to unify docs location...
Helmholtz codebase offers a runner with a Cavium ThunderX 88XX CPU with 12 cores with AArch64-architecture. Although there is no GPU available on this runner, I might make sense to...
**Related** currently the 10 functionality of matmul creates a matrix which is the size of the result on each process. this can be very dangerous if there is not enough...
**Description** When using indices to acces array elements the order in the result is not stable for different splits. **To Reproduce** ````` import heat as ht a = ht.array([0,1], split...