Release Scalable SVD, GSoC`22 contributions, Docker image, PyTorch 2 support, AMD GPUs acceleration · helmholtz-analytics/heat

This release includes many important updates (see below). We particularly would like to thank our enthusiastic GSoC2022 / tentative GSoC2023 contributors @Mystic-Slice @neosunhan @Sai-Suraj-27 @shahpratham @AsRaNi1 @Ishaan-Chandak 🙏🏼 Thank you so much!

Highlights

#1155 Support PyTorch 2.0.1 (by @ClaudiaComito)
#1152 Support AMD GPUs (by @mtar)
#1126 Distributed hierarchical SVD (by @mrfh92)
#1028 Introducing the sparse module: Distributed Compressed Sparse Row Matrix (by @Mystic-Slice)
Performance improvements:
- #1125 distributed heat.reshape() speed-up (by @ClaudiaComito)
- #1141 heat.pow() speed-up when exponent is int (by @ClaudiaComito @coquelin77 )
- #1119 heat.array() default to copy=None (e.g., only if necessary) (by @ClaudiaComito @neosunhan )
#970 Dockerfile and accompanying documentation (by @bhagemeier)

#1154 Introduce DNDarray.__array__() method for interoperability with numpy, xarray (by @ClaudiaComito)
#1147 Adopt NEP29, drop support for PyTorch 1.7, Python 3.6 (by @mtar)
#1119 ht.array() default to copy=None (e.g., only if necessary) (by @ClaudiaComito)
#1020 Implement broadcast_arrays, broadcast_to (by @neosunhan)
#1008 API: Rename keepdim kwarg to keepdims (by @neosunhan)
#788 Interface for DPPY interoperability (by @coquelin77 @fschlimb )

#1141 heat.pow() speed-up when exponent is int (by @ClaudiaComito)
#1136 Fixed PyTorch version check in sparse module (by @Mystic-Slice)
#1098 Validates number of dimensions in input to ht.sparse.sparse_csr_matrix (by @Ishaan-Chandak)
#1095 Convolve with distributed kernel on multiple GPUs (by @shahpratham)
#1094 Fix division precision error in random module (by @Mystic-Slice)
#1075 Fixed initialization of DNDarrays communicator in some routines (by @AsRaNi1)
#1066 Verify input object type and layout + Supporting tests (by @Mystic-Slice)
#1037 Distributed weighted average() along tuple of axes: shape of weights to match shape of input (by @Mystic-Slice)