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Merged
merged 2 commits into from
May 31, 2022
Merged

Release 0.4.0 #36

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1ba950b
Fix CI trigger and release instructions
cassiersg May 31, 2022
8051070
Release v0.4.0
cassiersg May 31, 2022
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2 changes: 2 additions & 0 deletions .github/workflows/ci.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,8 @@ on:
push:
branches:
- main
tags:
- v**
pull_request:
branches:
- main
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35 changes: 19 additions & 16 deletions CHANGELOG.rst
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Expand Up @@ -5,6 +5,9 @@ Changelog
Not released
------------

v0.4.0 (2022/05/31)
-------------------

* SASCA: support modular ADD and MUL operations (#18)
* TTest: Performance improvement by using a mix of 2 passes and 1 pass algorithms
* MTTest: First implementation of multivariate T-test.
Expand All @@ -15,55 +18,55 @@ Not released
* Revamp multi-threading handling thanks to new `scalib.threading` module.
* AVX2: Wheels on PyPi are built with AVX2 feature.

v0.3.4
------
v0.3.4 (2021/12/27)
-------------------

* Release GC in SASCA's `run_bp` .
* Release GC in `rank_accurary` and `rank_nbin`.
* `LDA.predict_proba` is marked thread-safe.
* Hide by default the progress bar of `SASCAGraph.run_bp` (can be re-enable
with the `progress` parameter).

v0.3.3
------
v0.3.3 (2021/07/13)
-------------------

* Solving minor issues in `MultiLDA` and `LDAClassifier`. Allowing multiple
threads in `predict_proba()` and add a `done` flag to `solve()`.

v0.3.2
------
v0.3.2 (2021/07/12)
-------------------

* Chunk `SNR.fit_u` to maintain similar performances with long traces and
adding a progress bar

v0.3.1
------
v0.3.1 (2021/06/03)
-------------------

* Add `max_nb_bin` parameter to `postprocessing.rank_accuracy` (that was
previously hard-coded).

v0.3.0
------
v0.3.0 (2021/06/01)
-------------------

* Rename `num_threads` parameter of `modeling.MultiLDA` to `num_cpus`.
* Fix rank estimation when there is only one key chunk.
* Improve performance of `SNR.get_snr`.

v0.2.0
------
v0.2.0 (2021/05/20)
-------------------

* Remove OpenBLAS and LAPACK, use Spectra and nalgebra instead.
* Use BLIS for matrix multiplications (Linux-only for now).
* Make `modeling.LDAClassifier` incremental (breaking change).
* Add `modeling.MultiLDA`.

v0.1.1
------
v0.1.1 (2021/04/26)
-------------------

* Fix "invalid instruction" bug for CI wheel on windows.

v0.1.0
------
v0.1.0 (2021/04/16)
-------------------

* Initial release, with the following features:
* LDA and Gaussian templates modelling
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10 changes: 10 additions & 0 deletions DEVELOP.rst
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Expand Up @@ -140,3 +140,13 @@ Also, when you develop, looking at generated assembly may help
RUSTFLAGS="-C target-feature=+avx2" cargo asm scalib::module::function --rust
# or
RUSTFLAGS="-C target-cpu=native" cargo asm scalib::module::function --rust

Make a release
--------------

0. Start from main branch
1. Add any missing element in CHANGELOG.rst
2. Add the new release with the release date in CHANGELOG.rst
3. Commit, create pull request and merge it (after CI succeeds).
4. Create and push release tag: `git tag vX.Y.Z && git push origin vX.Y.Z`