Software

FZJ-2023-05809

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png helmholtz-analytics/heat: Scalable SVD, GSoC`22 contributions, Docker image, PyTorch 2 support, AMD GPUs acceleration (v1.3.0)

Comito, C. (Corresponding author)FZJ* ; Coquelin, D. ; Tarnawa, M.FZJ* ; Götz, M. ; Blind, L. ; Debus, C. ; Hagemeier, B.FZJ* ; Krajsek, K.FZJ* ; Ohm, J. ; Hoppe, F. ; von der Lehr, F. ; Neo, S. H. ; Zutshi, A. ; Bourgart, B. ; Siggel, M. ; Ashwath, V. A. ; Schmitz, S. ; Gutiérrez Hermosillo Muriedas, J. P. ; Spataro, L. ; Markgraf, S. ; Shah, P. ; Suraj, S. ; Schlimbach, F. ; Glock, P. ; Kunjadiya, D. ; Ishaan-Chandak

2023

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Please use a persistent id in citations: doi:10.5281/ZENODO.8060498

Abstract: 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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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)

Appears in the scientific report 2023

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