[DOCS] Clarify that cooperative is for device, parallel for host (#522)

* [DOCS] Clarify that cooperative is for device, parallel for host

* Update README.md

* Remove dot at end

* Use language from README in cuda-python docs

---------

Co-authored-by: Ashwin Srinath <3190405+shwina@users.noreply.github.com>

Author: gmarkall

README.md

@@ -4,8 +4,8 @@ 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.cooperative](https://nvidia.github.io/cccl/cuda_cooperative/): Pythonic exposure of CUB cooperative algorithms
-* [cuda.parallel](https://nvidia.github.io/cccl/cuda_parallel/): Pythonic exposure of Thrust parallel algorithms
+* [cuda.cooperative](https://nvidia.github.io/cccl/cuda_cooperative/): A Python package for easy access to highly efficient and customizable parallel algorithms, like `sort`, `scan`, `reduce`, `transform`, etc.
+* [cuda.parallel](https://nvidia.github.io/cccl/cuda_parallel/): A Python package providing CUB's reusable block-wide and warp-wide primitives for use within Numba CUDA kernels
 
 For access to NVIDIA CPU & GPU Math Libraries, please refer to [nvmath-python](https://docs.nvidia.com/cuda/nvmath-python/latest).
 

cuda_python/docs/source/index.rst

@@ -6,8 +6,8 @@ multiple components:
 
 - `cuda.core`_: Pythonic access to CUDA runtime and other core functionalities
 - `cuda.bindings`_: Low-level Python bindings to CUDA C APIs
-- `cuda.cooperative`_: Pythonic exposure of CUB cooperative algorithms
-- `cuda.parallel`_: Pythonic exposure of Thrust parallel algorithms
+- `cuda.cooperative`_: A Python package for easy access to highly efficient and customizable parallel algorithms, like `sort`, `scan`, `reduce`, `transform`, etc.
+- `cuda.parallel`_: A Python package providing CUB's reusable block-wide and warp-wide primitives for use within Numba CUDA kernels
 
 For access to NVIDIA CPU & GPU Math Libraries, please refer to `nvmath-python`_.