TY  - COMP
AU  - Palazoglu, Berkant
AU  - Hoppe, Fabian
AU  - Scheib, Lukas
AU  - Tarnawa, Michael
AU  - Akdag, Hakan
AU  - Comito, Claudia
AU  - Gutiérrez Hermosillo Muriedas, Juan Pedro
AU  - Hees, Jörn
AU  - Jindra, Marc
AU  - Korten, Till
AU  - Krajsek, Kai
AU  - Lemmen, Jonas
AU  - Coquelin, Daniel
AU  - Debus, Charlotte
AU  - Hagemeier, Björn
AU  - Knechtges, Philipp
AU  - Rüttgers, Alexander
AU  - Götz, Markus
TI  - Heat (v1.7.0); 1.7.0
M1  - FZJ-2026-00696
PY  - 2025
AB  - <b>Overview</b><br>Version 1.7.0 introduces significant improvements in distributed data handling and numerical linear algebra, including a PyTorch-compatible DistributedSampler, randomized symmetric eigenvalue decomposition, and incremental SVD from HDF5. The release expands interoperability with partial Array API support and PyTorch 2.9.1, adds new distributed operations such as peak-to-peak, and delivers multiple robustness and device-placement bug fixes across MPI, GPU, and I/O workflows.<br>We are grateful to our community of users, students, open-source contributors, the European Space Agency, and the Helmholtz Association for their support and feedback.<br><br><b>Highlights</b><ul><li>DistributedSampler for efficient data loading and shuffling across multiple nodes with PyTorch</li><li>Randomized Symmetric eigenvalue decomposition (eigh)</li><li>Incremental SVD directly from an HDF5 file</li><li>Partial support of the Array API Standard (version: 2020.10), and API namespace under x.__array_namespace__(api_version='2020.10')</li><li>Distributed PTP (peak to peak) function</li></ul>
LB  - PUB:(DE-HGF)33
DO  - DOI:10.5281/ZENODO.18019822
UR  - https://juser.fz-juelich.de/record/1052023
ER  -