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Anerudhan merged 1 commit into from
Feb 18, 2026
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Update README to remove open-source kernel details #204

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11 changes: 0 additions & 11 deletions README.md
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# cuDNN FrontEnd(FE)

**cuDNN FE** is the modern, open-source entry point to the NVIDIA cuDNN library and high performance open-source kernels. It provides a C++ header-only library and a Python interface to access the powerful cuDNN Graph API and open-source kernels.

## 🚀 Embracing Open Source

We will begin open-sourcing kernels based on customer needs, with the goal to educate developers and enable them to customize as needed.

We are now shipping **OSS kernels**, allowing you to inspect, modify, and contribute to the core logic. Check out our latest implementations:

* **[GEMM + Amax](https://github.com/NVIDIA/cudnn-frontend/tree/main/python/cudnn/gemm_amax):** Optimized FP8 matrix multiplication with absolute maximum calculation.
* **[GEMM + SwiGLU](https://github.com/NVIDIA/cudnn-frontend/tree/main/python/cudnn/gemm_swiglu):** High-performance implementation of the SwiGLU activation fused with GEMM.
* **[NSA](https://github.com/NVIDIA/cudnn-frontend/tree/main/python/cudnn/native_sparse_attention/):** Native Sparse attention as described in the Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention.

## Key Features

* **Unified Graph API:** Create reusable, persistent `cudnn_frontend::graph::Graph` objects to describe complex subgraphs.
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