From db1c1cc784a37223dd861b7b0aa9d079798e07a4 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Wed, 14 Jan 2026 06:06:28 +0000 Subject: [PATCH 1/2] Initial plan From ad817c3a420d8edb3678cb164421ca68463fe9a7 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Wed, 14 Jan 2026 06:11:24 +0000 Subject: [PATCH 2/2] Add Accelerated Computing Hub to CUDA Python projects list Co-authored-by: leofang <5534781+leofang@users.noreply.github.com> --- README.md | 1 + cuda_python/DESCRIPTION.rst | 1 + cuda_python/docs/source/index.rst | 3 +++ 3 files changed, 5 insertions(+) diff --git a/README.md b/README.md index 2cbc40169a..6da895bbb9 100644 --- a/README.md +++ b/README.md @@ -13,6 +13,7 @@ CUDA Python is the home for accessing NVIDIA’s CUDA platform from Python. It c * [nvshmem4py](https://docs.nvidia.com/nvshmem/api/api/language_bindings/python/index.html): Pythonic interface to the NVSHMEM library, enabling Python applications to leverage NVSHMEM's high-performance PGAS (Partitioned Global Address Space) programming model for GPU-accelerated computing * [Nsight Python](https://docs.nvidia.com/nsight-python/index.html): Python kernel profiling interface that automates performance analysis across multiple kernel configurations using NVIDIA Nsight Tools * [CUPTI Python](https://docs.nvidia.com/cupti-python/): Python APIs for creation of profiling tools that target CUDA Python applications via the CUDA Profiling Tools Interface (CUPTI) +* [Accelerated Computing Hub](https://github.com/NVIDIA/accelerated-computing-hub): Open-source learning materials related to GPU computing. You will find user guides, tutorials, and other works freely available for all learners interested in GPU computing. CUDA Python is currently undergoing an overhaul to improve existing and introduce new components. All of the previously available functionality from the `cuda-python` package will continue to be available, please refer to the [cuda.bindings](https://nvidia.github.io/cuda-python/cuda-bindings/latest) documentation for installation guide and further detail. diff --git a/cuda_python/DESCRIPTION.rst b/cuda_python/DESCRIPTION.rst index 8edcad979e..6120a56802 100644 --- a/cuda_python/DESCRIPTION.rst +++ b/cuda_python/DESCRIPTION.rst @@ -18,6 +18,7 @@ CUDA Python is the home for accessing NVIDIA's CUDA platform from Python. It con * `nvshmem4py `_: Pythonic interface to the NVSHMEM library, enabling Python applications to leverage NVSHMEM's high-performance PGAS (Partitioned Global Address Space) programming model for GPU-accelerated computing * `Nsight Python `_: Python kernel profiling interface that automates performance analysis across multiple kernel configurations using NVIDIA Nsight Tools * `CUPTI Python `_: Python APIs for creation of profiling tools that target CUDA Python applications via the CUDA Profiling Tools Interface (CUPTI) +* `Accelerated Computing Hub `_: Open-source learning materials related to GPU computing. You will find user guides, tutorials, and other works freely available for all learners interested in GPU computing. CUDA Python is currently undergoing an overhaul to improve existing and introduce new components. All of the previously available functionality from the ``cuda-python`` package will continue to be available, please refer to the `cuda.bindings `_ documentation for installation guide and further detail. diff --git a/cuda_python/docs/source/index.rst b/cuda_python/docs/source/index.rst index f74b026871..7aad94ef9c 100644 --- a/cuda_python/docs/source/index.rst +++ b/cuda_python/docs/source/index.rst @@ -18,6 +18,7 @@ multiple components: - `nvshmem4py`_: Pythonic interface to the NVSHMEM library, enabling Python applications to leverage NVSHMEM's high-performance PGAS (Partitioned Global Address Space) programming model for GPU-accelerated computing - `Nsight Python`_: Python kernel profiling interface that automates performance analysis across multiple kernel configurations using NVIDIA Nsight Tools - `CUPTI Python`_: Python APIs for creation of profiling tools that target CUDA Python applications via the CUDA Profiling Tools Interface (CUPTI) +- `Accelerated Computing Hub`_: Open-source learning materials related to GPU computing. You will find user guides, tutorials, and other works freely available for all learners interested in GPU computing. .. _cuda.coop: https://nvidia.github.io/cccl/python/coop .. _cuda.compute: https://nvidia.github.io/cccl/python/compute @@ -31,6 +32,7 @@ multiple components: .. _nvshmem4py: https://docs.nvidia.com/nvshmem/api/api/language_bindings/python/index.html .. _Nsight Python: https://docs.nvidia.com/nsight-python/index.html .. _CUPTI Python: https://docs.nvidia.com/cupti-python/ +.. _Accelerated Computing Hub: https://github.com/NVIDIA/accelerated-computing-hub CUDA Python is currently undergoing an overhaul to improve existing and introduce new components. All of the previously available functionality from the ``cuda-python`` package will continue to @@ -56,3 +58,4 @@ be available, please refer to the `cuda.bindings`_ documentation for installatio nvshmem4py Nsight Python CUPTI Python + Accelerated Computing Hub