TY  - COMP
AU  - Comito, Claudia
AU  - Coquelin, Daniel
AU  - Tarnawa, Michael
AU  - Götz, Markus
AU  - Blind, Lena
AU  - Debus, Charlie
AU  - Hagemeier, Björn
AU  - Krajsek, Kai
AU  - Ohm, Jakob
AU  - Hoppe, Fabian
AU  - von der Lehr, Fabrice
AU  - Neo, Sun Han
AU  - Zutshi, Arnav
AU  - Bourgart, Benjamin
AU  - Siggel, Martin
AU  - Ashwath, V. A.
AU  - Schmitz, Simon
AU  - Gutiérrez Hermosillo Muriedas, Juan Pedro
AU  - Spataro, Luca
AU  - Markgraf, Sebastian
AU  - Shah, Pratham
AU  - Suraj, Sai
AU  - Schlimbach, Frank
AU  - Glock, Philipp
AU  - Kunjadiya, Dhruv
AU  - Ishaan-Chandak
TI  - helmholtz-analytics/heat: Scalable SVD, GSoC`22 contributions, Docker image, PyTorch 2 support, AMD GPUs acceleration (v1.3.0); 1.3.0
M1  - FZJ-2023-05809
PY  - 2023
AB  - 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) Changelog Array-API compliance / Interoperability #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 ) New Features #1126 Distributed hierarchical SVD (by @mrfh92) #1020 Implement broadcast_arrays , broadcast_to (by @neosunhan) #983 Signal processing: fully distributed 1D convolution (by @shahpratham) #1063 add eq to Device (by @mtar) Bug Fixes #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) Benchmarking #1137 Continous Benchmarking of runtime (by @JuanPedroGHM) Documentation #1150 Refactoring for efficiency and readability (by @Sai-Suraj-27) #1130 Reintroduce Quick Start (by @ClaudiaComito) #1079 A better README file (by @Sai-Suraj-27) Linear Algebra #1126, #1160 Distributed hierarchical SVD (by @mrfh92 @ClaudiaComito ) Contributors @AsRaNi1, @ClaudiaComito, @Ishaan-Chandak, @JuanPedroGHM, @Mystic-Slice, @Sai-Suraj-27, @bhagemeier, @coquelin77, @mrfh92, @mtar, @neosunhan, @shahpratham
LB  - PUB:(DE-HGF)33
DO  - DOI:10.5281/ZENODO.8060498
UR  - https://juser.fz-juelich.de/record/1019994
ER  -