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| Hauptseite > Publikationsdatenbank > helmholtz-analytics/heat: Scalable SVD, GSoC`22 contributions, Docker image, PyTorch 2 support, AMD GPUs acceleration (v1.3.0) > print |
| Hauptseite > Publikationsdatenbank > helmholtz-analytics/heat: Scalable SVD, GSoC`22 contributions, Docker image, PyTorch 2 support, AMD GPUs acceleration (v1.3.0) > print |
| 001 | 1019994 | ||
| 005 | 20240105202147.0 | ||
| 024 | 7 | _ | |a 10.5281/ZENODO.8060498 |2 doi |
| 037 | _ | _ | |a FZJ-2023-05809 |
| 100 | 1 | _ | |a Comito, Claudia |0 P:(DE-Juel1)174573 |b 0 |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 |2 DCMI |
| 336 | 7 | _ | |a Software |b sware |m sware |0 PUB:(DE-HGF)33 |s 1704431539_29017 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a MISC |2 BibTeX |
| 336 | 7 | _ | |a Computer Program |0 6 |2 EndNote |
| 336 | 7 | _ | |a OTHER |2 ORCID |
| 336 | 7 | _ | |a Software |2 DataCite |
| 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 |
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| 588 | _ | _ | |a Dataset connected to DataCite |
| 700 | 1 | _ | |a Coquelin, Daniel |0 P:(DE-Juel1)177671 |b 1 |
| 700 | 1 | _ | |a Tarnawa, Michael |0 P:(DE-Juel1)178977 |b 2 |
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