Chore/sync after move

CITATION.cff

@@ -2,7 +2,7 @@ cff-version: "1.2.0"
 date-released: 2025-06
 message: "If you use this software, please cite it using these metadata."
 title: "Flash Sparse Attention: Trainable Dynamic Mask Sparse Attention"
-url: "https://github.com/SmallDoges/flash-sparse-attention"
+url: "https://github.com/flash-algo/flash-sparse-attention"
 authors:
   - family-names: Shi
     given-names: Jingze

CONTRIBUTING.md

@@ -4,7 +4,7 @@ Everyone is welcome to contribute, and we value everybody's contribution. Code c
 
 It also helps us if you spread the word! Reference the library in blog posts about the awesome projects it made possible, shout out on Twitter every time it has helped you, or simply ⭐️ the repository to say thank you.
 
-However you choose to contribute, please be mindful and respect our [code of conduct](https://github.com/SmallDoges/flash-sparse-attention/blob/main/CODE_OF_CONDUCT.md).
+However you choose to contribute, please be mindful and respect our [code of conduct](https://github.com/flash-algo/flash-sparse-attention/blob/main/CODE_OF_CONDUCT.md).
 
 ## Ways to contribute
 
@@ -16,7 +16,7 @@ There are several ways you can contribute to Flash-DMA:
 * Contribute to the examples, benchmarks, or documentation.
 * Improve CUDA kernel performance.
 
-If you don't know where to start, there is a special [Good First Issue](https://github.com/SmallDoges/flash-sparse-attention/contribute) listing. It will give you a list of open issues that are beginner-friendly and help you start contributing to open-source.
+If you don't know where to start, there is a special [Good First Issue](https://github.com/flash-algo/flash-sparse-attention/contribute) listing. It will give you a list of open issues that are beginner-friendly and help you start contributing to open-source.
 
 > All contributions are equally valuable to the community. 🥰
 
@@ -81,14 +81,14 @@ You will need basic `git` proficiency to contribute to Flash-DMA. You'll need **
 
 ### Development Setup
 
-1. Fork the [repository](https://github.com/SmallDoges/flash-sparse-attention) by clicking on the **Fork** button.
+1. Fork the [repository](https://github.com/flash-algo/flash-sparse-attention) by clicking on the **Fork** button.
 
 2. Clone your fork to your local disk, and add the base repository as a remote:
 
    ```bash
    git clone https://github.com/<your Github handle>/flash-sparse-attention.git
    cd flash-sparse-attention
-   git remote add upstream https://github.com/SmallDoges/flash-sparse-attention.git
+   git remote add upstream https://github.com/flash-algo/flash-sparse-attention.git
    ```
 
 3. Create a new branch to hold your development changes:
@@ -157,7 +157,7 @@ You will need basic `git` proficiency to contribute to Flash-DMA. You'll need **
 
 ### Tests
 
-An extensive test suite is included to test the library behavior and performance. Tests can be found in the [tests](https://github.com/SmallDoges/flash-sparse-attention/tree/main/tests) folder and benchmarks in the [benchmarks](https://github.com/SmallDoges/flash-sparse-attention/tree/main/benchmarks) folder.
+An extensive test suite is included to test the library behavior and performance. Tests can be found in the [tests](https://github.com/flash-algo/flash-sparse-attention/tree/main/tests) folder and benchmarks in the [benchmarks](https://github.com/flash-algo/flash-sparse-attention/tree/main/benchmarks) folder.
 
 We use `pytest` for testing. From the root of the repository, run:
 
@@ -200,6 +200,6 @@ If you discover a security vulnerability, please send an e-mail to the maintaine
 
 ## Questions?
 
-If you have questions about contributing, feel free to ask in the [GitHub Discussions](https://github.com/SmallDoges/flash-sparse-attention/discussions) or open an issue.
+If you have questions about contributing, feel free to ask in the [GitHub Discussions](https://github.com/flash-algo/flash-sparse-attention/discussions) or open an issue.
 
 Thank you for contributing to Flash Sparse Attention! 🚀

README.md

@@ -1,5 +1,5 @@
 <!-- <div align="center">
-  <img src="./assets/logo.png" alt="SmallDoges" width="100%">
+  <img src="./assets/logo.png" alt="flash-algo" width="100%">
 </div> -->
 
 <div align="center">
@@ -67,7 +67,7 @@ pip install flash-sparse-attn --no-build-isolation
 Alternatively, you can compile and install from source:
 
 ```bash
-git clone https://github.com/SmallDoges/flash-sparse-attn.git
+git clone https://github.com/flash-algo/flash-sparse-attn.git
 cd flash-sparse-attn
 pip install . --no-build-isolation
 ```
@@ -293,8 +293,8 @@ We welcome contributions from the community! FSA is an open-source project and w
 
 ### How to Contribute
 
-- **Report bugs**: Found a bug? Please [open an issue](https://github.com/SmallDoges/flash_sparse_attn/issues/new/choose)
-- **Request features**: Have an idea for improvement? [Let us know](https://github.com/SmallDoges/flash_sparse_attn/issues/new/choose)
+- **Report bugs**: Found a bug? Please [open an issue](https://github.com/flash-algo/flash_sparse_attn/issues/new/choose)
+- **Request features**: Have an idea for improvement? [Let us know](https://github.com/flash-algo/flash_sparse_attn/issues/new/choose)
 - **Submit code**: Ready to contribute code? Check our [Contributing Guide](CONTRIBUTING.md)
 - **Improve docs**: Help us make the documentation better
 

README_zh.md

@@ -1,5 +1,5 @@
 <!-- <div align="center">
-  <img src="./assets/logo.png" alt="SmallDoges" width="100%">
+  <img src="./assets/logo.png" alt="flash-algo" width="100%">
 </div> -->
 
 <div align="center">
@@ -67,7 +67,7 @@ pip install flash-sparse-attn --no-build-isolation
 或者, 您可以从源代码编译和安装：
 
 ```bash
-git clone https://github.com/SmallDoges/flash-sparse-attn.git
+git clone https://github.com/flash-algo/flash-sparse-attn.git
 cd flash-sparse-attn
 pip install . --no-build-isolation
 ```
@@ -292,8 +292,8 @@ python benchmarks/grad_equivalence.py
 
 ### 如何贡献
 
-- **报告错误**: 发现了错误？请[提交 issue](https://github.com/SmallDoges/flash_sparse_attn/issues/new/choose)
-- **功能请求**: 有改进想法？[告诉我们](https://github.com/SmallDoges/flash_sparse_attn/issues/new/choose)
+- **报告错误**: 发现了错误？请[提交 issue](https://github.com/flash-algo/flash_sparse_attn/issues/new/choose)
+- **功能请求**: 有改进想法？[告诉我们](https://github.com/flash-algo/flash_sparse_attn/issues/new/choose)
 - **提交代码**: 准备贡献代码？查看我们的[贡献指南](CONTRIBUTING.md)
 - **改进文档**: 帮助我们完善文档
 

SECURITY.md

@@ -50,7 +50,7 @@ If you discover a security vulnerability, please report it responsibly:
 - Include: Detailed description, reproduction steps, and potential impact
 
 **For general bugs:**
-- Use our [GitHub Issues](https://github.com/SmallDoges/flash-sparse-attention/issues)
+- Use our [GitHub Issues](https://github.com/flash-algo/flash-sparse-attention/issues)
 - Follow our [contributing guidelines](CONTRIBUTING.md)
 
 ## Response Timeline
@@ -108,5 +108,5 @@ For security-related questions or concerns:
 - Project maintainers: See [AUTHORS](AUTHORS) file
 
 For general support:
-- GitHub Issues: https://github.com/SmallDoges/flash-sparse-attention/issues
-- Documentation: https://github.com/SmallDoges/flash-sparse-attention/tree/main/docs/
+- GitHub Issues: https://github.com/flash-algo/flash-sparse-attention/issues
+- Documentation: https://github.com/flash-algo/flash-sparse-attention/tree/main/docs/

pyproject.toml

@@ -40,9 +40,9 @@ classifiers = [
 ]
 
 [project.urls]
-Homepage = "https://github.com/SmallDoges/flash-sparse-attention"
-Source = "https://github.com/SmallDoges/flash-sparse-attention"
-Issues = "https://github.com/SmallDoges/flash-sparse-attention/issues"
+Homepage = "https://github.com/flash-algo/flash-sparse-attention"
+Source = "https://github.com/flash-algo/flash-sparse-attention"
+Issues = "https://github.com/flash-algo/flash-sparse-attention/issues"
 
 [project.optional-dependencies]
 triton = [

setup.py

@@ -37,7 +37,7 @@
 PACKAGE_NAME = "flash_sparse_attn"
 
 BASE_WHEEL_URL = (
-    "https://github.com/SmallDoges/flash-sparse-attention/releases/download/{tag_name}/{wheel_name}"
+    "https://github.com/flash-algo/flash-sparse-attention/releases/download/{tag_name}/{wheel_name}"
 )
 
 # FORCE_BUILD: Force a fresh build locally, instead of attempting to find prebuilt wheels