# Third-party notices
Ruda reuses some operators and optimization implementations from open-source projects such as CubeCL and Burn. The relevant code retains its original copyright and license notices.
Ruda 复用了 CubeCL、Burn 等开源项目的部分算子和优化实现。相关代码保留其原有版权及许可证声明。
## ruda-core/LICENSE-APACHE, ruda-ir-macros/LICENSE-APACHE
Apache License
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APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
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Copyright 2022 Nathaniel Simard & CubeCl Framework Contributors
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
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See the License for the specific language governing permissions and
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## ruda-core/LICENSE-MIT, ruda-ir-macros/LICENSE-MIT
MIT License
Copyright (c) 2022 Nathaniel Simard & CubeCL Framework Contributors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
## ruda-dataset/LICENSE-APACHE, ruda-tensor-tch/LICENSE-APACHE, ruda-tensor-wgpu/LICENSE-APACHE
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
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"Source" form shall mean the preferred form for making modifications,
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of this License, Derivative Works shall not include works that remain
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the Work and Derivative Works thereof.
"Contribution" shall mean any work of authorship, including
the original version of the Work and any modifications or additions
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or by an individual or Legal Entity authorized to submit on behalf of
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to the Licensor or its representatives, including but not limited to
communication on electronic mailing lists, source code control systems,
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Licensor for the purpose of discussing and improving the Work, but
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designated in writing by the copyright owner as "Not a Contribution."
"Contributor" shall mean Licensor and any individual or Legal Entity
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2. Grant of Copyright License. Subject to the terms and conditions of
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copyright license to reproduce, prepare Derivative Works of,
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Work and such Derivative Works in Source or Object form.
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worldwide, non-exclusive, no-charge, royalty-free, irrevocable
(except as stated in this section) patent license to make, have made,
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where such license applies only to those patent claims licensable
by such Contributor that are necessarily infringed by their
Contribution(s) alone or by combination of their Contribution(s)
with the Work to which such Contribution(s) was submitted. If You
institute patent litigation against any entity (including a
cross-claim or counterclaim in a lawsuit) alleging that the Work
or a Contribution incorporated within the Work constitutes direct
or contributory patent infringement, then any patent licenses
granted to You under this License for that Work shall terminate
as of the date such litigation is filed.
4. Redistribution. You may reproduce and distribute copies of the
Work or Derivative Works thereof in any medium, with or without
modifications, and in Source or Object form, provided that You
meet the following conditions:
(a) You must give any other recipients of the Work or
Derivative Works a copy of this License; and
(b) You must cause any modified files to carry prominent notices
stating that You changed the files; and
(c) You must retain, in the Source form of any Derivative Works
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excluding those notices that do not pertain to any part of
the Derivative Works; and
(d) If the Work includes a "NOTICE" text file as part of its
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of the NOTICE file are for informational purposes only and
do not modify the License. You may add Your own attribution
notices within Derivative Works that You distribute, alongside
or as an addendum to the NOTICE text from the Work, provided
that such additional attribution notices cannot be construed
as modifying the License.
You may add Your own copyright statement to Your modifications and
may provide additional or different license terms and conditions
for use, reproduction, or distribution of Your modifications, or
for any such Derivative Works as a whole, provided Your use,
reproduction, and distribution of the Work otherwise complies with
the conditions stated in this License.
5. Submission of Contributions. Unless You explicitly state otherwise,
any Contribution intentionally submitted for inclusion in the Work
by You to the Licensor shall be under the terms and conditions of
this License, without any additional terms or conditions.
Notwithstanding the above, nothing herein shall supersede or modify
the terms of any separate license agreement you may have executed
with Licensor regarding such Contributions.
6. Trademarks. This License does not grant permission to use the trade
names, trademarks, service marks, or product names of the Licensor,
except as required for reasonable and customary use in describing the
origin of the Work and reproducing the content of the NOTICE file.
7. Disclaimer of Warranty. Unless required by applicable law or
agreed to in writing, Licensor provides the Work (and each
Contributor provides its Contributions) on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied, including, without limitation, any warranties or conditions
of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
PARTICULAR PURPOSE. You are solely responsible for determining the
appropriateness of using or redistributing the Work and assume any
risks associated with Your exercise of permissions under this License.
8. Limitation of Liability. In no event and under no legal theory,
whether in tort (including negligence), contract, or otherwise,
unless required by applicable law (such as deliberate and grossly
negligent acts) or agreed to in writing, shall any Contributor be
liable to You for damages, including any direct, indirect, special,
incidental, or consequential damages of any character arising as a
result of this License or out of the use or inability to use the
Work (including but not limited to damages for loss of goodwill,
work stoppage, computer failure or malfunction, or any and all
other commercial damages or losses), even if such Contributor
has been advised of the possibility of such damages.
9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
and charge a fee for, acceptance of support, warranty, indemnity,
or other liability obligations and/or rights consistent with this
License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
replaced with your own identifying information. (Don't include
the brackets!) The text should be enclosed in the appropriate
comment syntax for the file format. We also recommend that a
file or class name and description of purpose be included on the
same "printed page" as the copyright notice for easier
identification within third-party archives.
Copyright 2022 Nathaniel Simard & Burn Framework Contributors
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
## ruda-dataset/LICENSE-MIT, ruda-tensor-tch/LICENSE-MIT, ruda-tensor-wgpu/LICENSE-MIT
MIT License
Copyright (c) 2022 Nathaniel Simard & Burn Framework Contributors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
## ruda-hip-sys
Source: cubecl-hip-sys 7.14.6085000, commit `99b002ee9ac7907d3c6c6eb80fd3e5c91c237976`, `crates/cubecl-hip-sys`.
MIT License
Copyright (c) 2024 Tracel Technologies Inc. and Contributors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
- https://github.com/tracel-ai/burn/issues/2676
- https://github.com/tracel-ai/burn/issues/2739
- https://github.com/tracel-ai/burn/issues/3754
- https://github.com/tracel-ai/burn/issues/4179
- https://github.com/tracel-ai/burn/issues/4362
- https://github.com/tracel-ai/burn/issues/4762
- https://github.com/tracel-ai/burn/pull/3792#discussion_r2416812091
- https://github.com/tracel-ai/burn/tree/main/crates/burn-tch
- https://github.com/tracel-ai/cubecl-hip/tree/main/crates/cubecl-hip-sys
- https://github.com/tracel-ai/cubecl/issues/1120
- https://github.com/tracel-ai/cubecl/pull/1312
- https://github.com/tracel-ai/cubek/issues/194
## Muon integration additions (2026-09-10)
The Muon implementation in ruda-optim already exists in the supplied baseline and
retains its original RUDA/Burn-derived provenance and package license. This patch
adds explicit parameter routing, validation, numerical options and tests; it does
not relabel the existing optimizer as a newly invented algorithm. New files carry
an Apache-2.0 SPDX identifier. No upstream Python source file is bundled.
Algorithm references: Keller Jordan et al., Muon (https://github.com/KellerJordan/Muon),
and PyTorch's fixed v2.9 implementation
(https://github.com/pytorch/pytorch/blob/v2.9.0/torch/optim/_muon.py).
The learning-rate option MatchRmsAdamW refers to Moonshot's
Muon is Scalable for LLM Training (https://arxiv.org/abs/2502.16982).
The numerical oracle additionally calls the locally installed, unmodified
torch.optim.Muon. Its source hash/version are recorded in the validation results;
the installed PyTorch source is not redistributed with this patch.
## ruSOLVER / ruINTEGRATE numerical science addition (2026-09-10)
The new solver/integrator sources are independently written Rust implementations of published numerical methods, not copies of LAPACK, cuSOLVER, SciPy or GSL source. Mathematical coefficients and method references are documented in `docs/en/libraries/rusolver.md` and `ruintegrate.md`. `tools/science/oracle.py` calls NumPy/SciPy only to generate/check independent test expectations; these are not runtime dependencies of the Rust libraries. The optional `rusolver/sparse` feature borrows the existing ruSPARSE types and does not change their license. Existing tensor-level LU remains unchanged.
## Extended numerical science implementation (2026-09-10)
New `ruSOLVER` SVD, complex, sparse direct, distributed-CG, pullback and device
kernels, plus `ruINTEGRATE` stiff/events/improper-integral sources are independent
Rust implementations of standard mathematical methods. They are not copies of
LAPACK, SuperLU, SciPy, GSL or PyTorch implementation source. Existing RUDA graph,
Host backend, compiler and ruCCL integration retain their original provenance.
New sources use Apache-2.0 SPDX identifiers; existing notices are not removed.
Method/behavior references:
- LAPACK one-sided Jacobi SVD, DGESVJ: https://www.netlib.org/lapack/explore-html/d9/deb/group__gesvj.html
- LAPACK complex Householder QR, ZGEQRF: https://www.netlib.org/lapack/explore-html/d0/da1/group__geqrf.html
- SciPy initial-value ODE methods/events: https://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.solve_ivp.html
- SciPy infinite-domain quadrature: https://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.quad.html
- PyTorch linear-algebra autodiff: https://pytorch.org/blog/torch-linalg-autograd/
- PyTorch SVD differentiation restrictions: https://docs.pytorch.org/docs/stable/generated/torch.linalg.svd.html
`tools/science_extended/oracle.py` calls installed NumPy/SciPy/PyTorch as external
numerical oracles and generates small independent fixtures. These packages are
not host solver runtime dependencies and their source is not distributed here.
The FP32 recurrence model is Python arithmetic, not execution of a RUDA kernel.