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Author: vlad-perevezentsev

CHANGELOG.md

@@ -8,7 +8,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
-* Added support for selecting CUDA architecture via the `--target-cuda` option using [CodePlay oneAPI plug-in](https://developer.codeplay.com/products/oneapi/nvidia/home/) [#2478](https://github.com/IntelPython/dpnp/pull/2478)
+* Added `--target-cuda[=ARCH]` option to replace the deprecated `--target=cuda`, allowing users to build for CUDA devices with optional architecture selection using [CodePlay oneAPI plug-in](https://developer.codeplay.com/products/oneapi/nvidia/home/) [#2478](https://github.com/IntelPython/dpnp/pull/2478)
 
 ### Changed
 

doc/quick_start_guide.rst

@@ -165,8 +165,8 @@ To use the default architecture (``sm_50``), run:
 
     python scripts/build_locally.py --target-cuda
 
-Note that kernels are built for ``sm_50`` by default, allowing them to work on a wider
-range of architectures, but limiting the usage of more recent CUDA features.
+Note that kernels are built for the default architecture (``sm_50``), allowing them to work on a
+wider range of architectures, but limiting the usage of more recent CUDA features.
 
 For reference, compute architecture strings like ``sm_80`` correspond to specific
 CUDA Compute Capabilities (e.g., Compute Capability 8.0 corresponds to ``sm_80``).
@@ -203,8 +203,8 @@ For example:
 Multi-target build
 ~~~~~~~~~~~~~~~~~~
 
-It is, however, possible to build for Intel devices, CUDA devices, and an AMD device
-architecture all at once:
+By default, building from source enables support for Intel devices.
+However, the build can be extended to support both CUDA and AMD devices simultaneously:
 
 .. code-block:: bash