Merge branch 'main' into faster_set_current

Author: leofang

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -38,6 +38,7 @@ body:
       description: Which cuda-python component does this apply to?
       multiple: false
       options:
+        - cuda.pathfinder
         - cuda.bindings
         - cuda.core
         - General cuda-python

.github/ISSUE_TEMPLATE/feature_request.yml

@@ -22,6 +22,7 @@ body:
       description: What area does this request apply to?
       multiple: false
       options:
+        - cuda.pathfinder
         - cuda.bindings
         - cuda.core
         - General cuda-python

README.md

@@ -5,23 +5,23 @@ CUDA Python is the home for accessing NVIDIA’s CUDA platform from Python. It c
 * [cuda.core](https://nvidia.github.io/cuda-python/cuda-core/latest): Pythonic access to CUDA Runtime and other core functionalities
 * [cuda.bindings](https://nvidia.github.io/cuda-python/cuda-bindings/latest): Low-level Python bindings to CUDA C APIs
 * [cuda.cccl.cooperative](https://nvidia.github.io/cccl/cuda_cooperative/): A Python module providing CCCL's reusable block-wide and warp-wide *device* primitives for use within Numba CUDA kernels
-* [cuda.cccl.parallel](https://nvidia.github.io/cccl/cuda_parallel/): A Python module for easy access to CCCL's highly efficient and customizable parallel algorithms, like `sort`, `scan`, `reduce`, `transform`, etc, that are callable on the *host*
+* [cuda.cccl.parallel](https://nvidia.github.io/cccl/cuda_parallel/): A Python module for easy access to CCCL's highly efficient and customizable parallel algorithms, like `sort`, `scan`, `reduce`, `transform`, etc. that are callable on the *host*
 * [numba.cuda](https://nvidia.github.io/numba-cuda/): Numba's target for CUDA GPU programming by directly compiling a restricted subset of Python code into CUDA kernels and device functions following the CUDA execution model.
 * [nvmath-python](https://docs.nvidia.com/cuda/nvmath-python/latest): Pythonic access to NVIDIA CPU & GPU Math Libraries, with both [*host*](https://docs.nvidia.com/cuda/nvmath-python/latest/overview.html#host-apis) and [*device* (nvmath.device)](https://docs.nvidia.com/cuda/nvmath-python/latest/overview.html#device-apis) APIs. It also provides low-level Python bindings to host C APIs ([nvmath.bindings](https://docs.nvidia.com/cuda/nvmath-python/latest/bindings/index.html)).
 
-CUDA Python is currently undergoing an overhaul to improve existing and bring up new components. All of the previously available functionalities 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.
+CUDA Python is currently undergoing an overhaul to improve existing and introduce new components. All of the previously available functionalities 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.
 
 ## cuda-python as a metapackage
 
-`cuda-python` is being re-structured to become a metapackage that contains a collection of subpackages. Each subpackage is versioned independently, allowing installation of each component as needed.
+`cuda-python` is being restructured to become a metapackage that contains a collection of subpackages. Each subpackage is versioned independently, allowing installation of each component as needed.
 
 ### Subpackage: `cuda.core`
 
-The `cuda.core` package offers idiomatic, pythonic access to CUDA Runtime and other functionalities.
+The `cuda.core` package offers idiomatic, Pythonic access to CUDA Runtime and other functionalities.
 
 The goals are to
 
-1. Provide **idiomatic ("pythonic")** access to CUDA Driver, Runtime, and JIT compiler toolchain
+1. Provide **idiomatic ("Pythonic")** access to CUDA Driver, Runtime, and JIT compiler toolchain
 2. Focus on **developer productivity** by ensuring end-to-end CUDA development can be performed quickly and entirely in Python
 3. **Avoid homegrown** Python abstractions for CUDA for new Python GPU libraries starting from scratch
 4. **Ease** developer **burden of maintaining** and catching up with latest CUDA features
@@ -31,7 +31,7 @@ The goals are to
 
 The `cuda.bindings` package is a standard set of low-level interfaces, providing full coverage of and access to the CUDA host APIs from Python.
 
-The list of available interfaces are:
+The list of available interfaces is:
 
 * CUDA Driver
 * CUDA Runtime

SECURITY.md

@@ -6,9 +6,9 @@ including all source code repositories managed through our organization.
 If you need to report a security issue, please use the appropriate contact points outlined
 below. **Please do not report security vulnerabilities through GitHub/GitLab.**
 
-## Reporting Potential Security Vulnerability in nvmath-python
+## Reporting Potential Security Vulnerability in CUDA Python
 
-To report a potential security vulnerability in nvmath-python:
+To report a potential security vulnerability in CUDA Python:
 
 - Web: [Security Vulnerability Submission
   Form](https://www.nvidia.com/object/submit-security-vulnerability.html)