Heat 1.5.0-rc1: Pre-Release

Changes

Cluster

• #1593 Improved Batch Parallelization. (by @mrfh92)

Data

• #1529 Make dataset.ishuffle optional. (by @krajsek)

IO

• #1602 Improved load balancing when loading .npy files from path. (by @Reisii)
• #1551 Improved load balancing when loading .csv files from path. (by @Reisii)

Linear Algebra

• #1261 Batched matrix multiplication. (by @FOsterfeld)
• #1504 Add solver for triangular systems. (by @FOsterfeld)

Manipulations

• #1419 Implement distributed unfold operation. (by @FOsterfeld)

Random

• #1508 Introduce Batchparallel for RNG as default. (by @mrfh92)

Signal

• #1515 Support batch 1-d convolution in ht.signal.convolve. (by @ClaudiaComito)

Statistics

• #1510 Support multiple axes for ht.percentile. (by @ClaudiaComito)

Sparse

• #1377 Distributed Compressed Sparse Column Matrix. (by @Mystic-Slice)

Other

• #1618 Support mpi4py 4.x.x (by @JuanPedroGHM)

Contributors

@ClaudiaComito, @FOsterfeld, @JuanPedroGHM, @Reisii, @mrfh92, @mtar and @krajsek

Heat 1.4.2 - Maintenance Release

Changes

Interoperability

• #1467, #1525 Support PyTorch 2.3.1 (by @mtar)
• #1535 Address test failures after netCDF4 1.7.1, numpy 2 releases (by @ClaudiaComito)

Contributors

@ClaudiaComito, @mrfh92 and @mtar

Heat 1.4.1: Bug fix release

Changes

Bug fixes

• #1472 DNDarrays returned by _like functions default to same device as input DNDarray (by @mrfh92, @ClaudiaComito)

Maintenance

• #1441 added names of non-core members in citation file (by @mrfh92)

Contributors

@ClaudiaComito and @mrfh92

Interactive HPC tutorials, distributed FFT, batch-parallel clustering, support PyTorch 2.2.2

Changes

Documentation

• #1406 New tutorials for interactive parallel mode for both HPC and local usage (by @ClaudiaComito)

🔥 Features

• #1288 Batch-parallel K-means and K-medians (by @mrfh92)
• #1228 Introduce in-place-operators for arithmetics.py (by @LScheib)
• #1218 Distributed Fast Fourier Transforms (by @ClaudiaComito)

Bug fixes

• #1363 ht.array constructor respects implicit torch device when copy is set to false (by @JuanPedroGHM)
• #1216 Avoid unnecessary gathering of distributed operand (by @samadpls)
• #1329 Refactoring of QR: stabilized Gram-Schmidt for split=1 and TS-QR for split=0 (by @mrfh92)

Interoperability

• #1418 and #1290: Support PyTorch 2.2.2 (by @mtar)
• #1315 and #1337: Fix some NumPy deprecations in the core and statistics tests (by @FOsterfeld)

Contributors

@ClaudiaComito, @FOsterfeld, @JuanPedroGHM, @LScheib, @mrfh92, @mtar, @samadpls

Bug fixes, Docker documentation update

Bug fixes

• #1259 Bug-fix for ht.regression.Lasso() on GPU (by @mrfh92)
• #1201 Fix ht.diff for 1-element-axis edge case (by @mtar)

Changes

Interoperability

• #1257 Docker release 1.3.x update (by @JuanPedroGHM)

Maintenance

• #1274 Update version before release (by @ClaudiaComito)
• #1267 Unit tests: Increase tolerance for ht.allclose on ht.inv operations for all torch versions (by @ClaudiaComito)
• #1266 Sync pre-commit configuration with main branch (by @ClaudiaComito)
• #1264 Fix Pytorch release tracking workflows (by @mtar)
• #1234 Update sphinx package requirements (by @mtar)
• #1187 Create configuration file for Read the Docs (by @mtar)

Contributors

@ClaudiaComito, @JuanPedroGHM, @bhagemeier, @mrfh92 and @mtar

Scalable SVD, GSoC`22 contributions, Docker image, PyTorch 2 support, AMD GPUs acceleration

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

Bug fixes, support OpenMPI>=4.1.2, support PyTorch 1.13.1

Changes

Communication

• #1058 Fix edge-case contiguity mismatch for Allgatherv (by @ClaudiaComito)

Contributors

@ClaudiaComito, @JuanPedroGHM

Support PyTorch 1.13, Lanczos decomposition fix, bug fixes

Changes

• #1048 Support PyTorch 1.13.0 on branch release/1.2.x (by @github-actions)

🐛 Bug Fixes

• #1038 Lanczos decomposition linalg.solver.lanczos: Support double precision, complex data types (by @ClaudiaComito)
• #1034 ht.array, closed loophole allowing DNDarray construction with incompatible shapes of local arrays (by @Mystic-Slice)

Linear Algebra

• #1038 Lanczos decomposition linalg.solver.lanczos: Support double precision, complex data types (by @ClaudiaComito)

🧪 Testing

• #1025 mirror repository on gitlab + ci (by @mtar)
• #1014 fix: set cuda rng state on gpu tests for test_random.py (by @JuanPedroGHM)

Contributors

@ClaudiaComito, @JuanPedroGHM, @Mystic-Slice, @coquelin77, @mtar, @github-actions, @github-actions[bot]

v1.2.0: GSoC22, introducing `signal` module, parallel I/O and more

Highlights

• We have been selected as a mentoring organization for Google Summer of Code, and we already have many new contributors (see below). Thank you!
• Heat now supports PyTorch 1.11
• Gearing up to support data-intensive signal processing: introduced signal module and memory-distributed 1-D convolution with ht.convolve()
• Parallel I/O: you can now parallelize writing out to CSV file with ht.save_csv().
• Introduced more flexibility in memory-distributed binary operations.
• Expanded functionalities in linalg, manipulations modules.

What's Changed

• Bug/825 setitem slice dndarrays by @coquelin77 in #826
• Features/807 roll by @mtar in #829
• implement vecdot by @mtar in #840
• Enhancement/798 logical dndarrray by @mtar in #851
• add moveaxis by @mtar in #854
• add swapaxes by @mtar in #853
• norm implementation by @mtar in #846
• Features/178 tile by @ClaudiaComito in #673
• Features/torch proxy by @ClaudiaComito in #856
• add normal, standard_normal by @mtar in #858
• add signbit by @mtar in #862
• add sign, sgn by @mtar in #827
• vdot implementation by @mtar in #842
• Bugfix/529 lasso example by @bhagemeier in #876
• fix binary_op on operands with single element by @mtar in #868
• conjugate method in DNDarray by @mtar in #885
• add cross by @mtar in #850
• Feature/337 determinant by @mtar in #877
• Features/746 print0 print toggle by @coquelin77 in #816
• Feature/338 matrix inverse by @mtar in #875
• randint accept ints for 'size' by @mtar in #916
• Support PyTorch 1.11.0 by @github-actions in #932
• 750 save csv v2 by @bhagemeier in #941
• added duplicate comm by @Dhruv454000 in #940
• changed documentation small fix by @Dhruv454000 in #956
• add digitize/bucketize by @mtar in #928
• Improve save_csv string formatting by @bhagemeier in #948
• Random: Replaced factories.array with DNDarray by @shahpratham in #960
• Features/30 convolve by @lucaspataro in #595
• Add out and where args for ht.div by @neosunhan in #945

New Contributors

• @Dhruv454000 made their first contribution in #940
• @shahpratham made their first contribution in #960
• @neosunhan made their first contribution in #945

Full Changelog: v1.1.0...v1.2.0

Tuning dependencies, minor documentation edits

v1.1.1

• #864 Dependencies: constrain torchvision version range to match supported pytorch version range.