001     1019994
005     20240105202147.0
024 7 _ |a 10.5281/ZENODO.8060498
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037 _ _ |a FZJ-2023-05809
100 1 _ |a Comito, Claudia
|0 P:(DE-Juel1)174573
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|e Corresponding author
245 _ _ |a helmholtz-analytics/heat: Scalable SVD, GSoC`22 contributions, Docker image, PyTorch 2 support, AMD GPUs acceleration (v1.3.0)
250 _ _ |a 1.3.0
260 _ _ |c 2023
336 7 _ |a Software
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336 7 _ |a Computer Program
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336 7 _ |a OTHER
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336 7 _ |a Software
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520 _ _ |a 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
536 _ _ |a 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)
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700 1 _ |a Coquelin, Daniel
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700 1 _ |a Tarnawa, Michael
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700 1 _ |a Götz, Markus
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700 1 _ |a Blind, Lena
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700 1 _ |a Debus, Charlie
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700 1 _ |a Hagemeier, Björn
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700 1 _ |a Krajsek, Kai
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700 1 _ |a Ohm, Jakob
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700 1 _ |a Hoppe, Fabian
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700 1 _ |a von der Lehr, Fabrice
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700 1 _ |a Neo, Sun Han
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700 1 _ |a Zutshi, Arnav
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700 1 _ |a Bourgart, Benjamin
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700 1 _ |a Siggel, Martin
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700 1 _ |a Ashwath, V. A.
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700 1 _ |a Schmitz, Simon
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700 1 _ |a Gutiérrez Hermosillo Muriedas, Juan Pedro
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700 1 _ |a Spataro, Luca
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700 1 _ |a Markgraf, Sebastian
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700 1 _ |a Shah, Pratham
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700 1 _ |a Suraj, Sai
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700 1 _ |a Schlimbach, Frank
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700 1 _ |a Glock, Philipp
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700 1 _ |a Kunjadiya, Dhruv
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700 1 _ |a Ishaan-Chandak
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