patch 'doc: improve wording of cuda guide' has been queued to stable release 22.11.3

[Xueming Li]

Hi,

FYI, your patch has been queued to stable release 22.11.3

Note it hasn't been pushed to http://dpdk.org/browse/dpdk-stable yet.
It will be pushed if I get no objections before 08/11/23. So please
shout if anyone has objections.

Also note that after the patch there's a diff of the upstream commit vs the
patch applied to the branch. This will indicate if there was any rebasing
needed to apply to the stable branch. If there were code changes for rebasing
(ie: not only metadata diffs), please double check that the rebase was
correctly done.

Queued patches are on a temporary branch at:
https://git.dpdk.org/dpdk-stable/log/?h=22.11-staging

This queued commit can be viewed at:
https://git.dpdk.org/dpdk-stable/commit/?h=22.11-staging&id=fdb81fcc2ceb4cfd4271cd650c2cd3748e370cf7

Thanks.

Xueming Li <xuemingl at nvidia.com>

---
>From fdb81fcc2ceb4cfd4271cd650c2cd3748e370cf7 Mon Sep 17 00:00:00 2001
From: Ali Alnubani <alialnu at nvidia.com>
Date: Mon, 3 Jul 2023 11:14:23 +0300
Subject: [PATCH] doc: improve wording of cuda guide
Cc: Xueming Li <xuemingl at nvidia.com>

[ upstream commit 135551ae0bae5a9e575b0a531490c24ef730dac0 ]

Adds missing punctuation, and improves wording.
Additionally, one of the example commands for adding CUDA
headers to CFLAGS is removed as it's redundant.

Fixes: 24c77594e08f ("gpu/cuda: map GPU memory with GDRCopy")
Fixes: 1306a73b1958 ("gpu/cuda: introduce CUDA driver")

Signed-off-by: Ali Alnubani <alialnu at nvidia.com>
---
 doc/guides/gpus/cuda.rst | 28 ++++++++++++++--------------
 1 file changed, 14 insertions(+), 14 deletions(-)

diff --git a/doc/guides/gpus/cuda.rst b/doc/guides/gpus/cuda.rst
index 114e3bc8cb..6520c17c3e 100644
--- a/doc/guides/gpus/cuda.rst
+++ b/doc/guides/gpus/cuda.rst
@@ -12,20 +12,19 @@ Information and documentation about these devices can be found on the
 Build dependencies
 ------------------
 
-The CUDA GPU driver library has an header-only dependency on ``cuda.h`` and ``cudaTypedefs.h``.
-To get these headers there are two options:
+The CUDA GPU driver library has a header-only dependency on ``cuda.h`` and ``cudaTypedefs.h``.
+To get these headers, there are two options:
 
 - Install `CUDA Toolkit <https://developer.nvidia.com/cuda-toolkit>`_
   (either regular or stubs installation).
 - Download these two headers from this `CUDA headers
   <https://gitlab.com/nvidia/headers/cuda-individual/cudart>`_ repository.
 
-You need to indicate to meson where CUDA headers files are through the CFLAGS variable.
-Three ways:
+You can point to CUDA header files either with the ``CFLAGS`` environment variable,
+or with the ``c_args`` Meson option. Examples:
 
-- Set ``export CFLAGS=-I/usr/local/cuda/include`` before building
-- Add CFLAGS in the meson command line ``CFLAGS=-I/usr/local/cuda/include meson setup build``
-- Add the ``-Dc_args`` in meson command line ``meson setup build -Dc_args=-I/usr/local/cuda/include``
+- ``CFLAGS=-I/usr/local/cuda/include meson setup build``
+- ``meson setup build -Dc_args=-I/usr/local/cuda/include``
 
 If headers are not found, the CUDA GPU driver library is not built.
 
@@ -46,15 +45,15 @@ A quick recipe to download, build and run GDRCopy library and driver:
   $ # Launch gdrdrv kernel module on the system
   $ sudo ./insmod.sh
 
-You need to indicate to meson where GDRCopy headers files are as in case of CUDA headers.
+You need to indicate to Meson where GDRCopy header files are as in case of CUDA headers.
 An example would be:
 
 .. code-block:: console
 
   $ meson setup build -Dc_args="-I/usr/local/cuda/include -I/path/to/gdrcopy/include"
 
-If headers are not found, the CUDA GPU driver library is built without the CPU map capability
-and will return error if the application invokes the gpudev ``rte_gpu_mem_cpu_map`` function.
+If headers are not found, the CUDA GPU driver library is built without the CPU map capability,
+and will return an error if the application invokes the gpudev ``rte_gpu_mem_cpu_map`` function.
 
 
 CUDA Shared Library
@@ -143,7 +142,7 @@ if the address is not in the table the CUDA driver library will return an error.
 Features
 --------
 
-- Register new child devices aka new CUDA Driver contexts.
+- Register new child devices, aka CUDA driver contexts.
 - Allocate memory on the GPU.
 - Register CPU memory to make it visible from GPU.
 
@@ -189,9 +188,10 @@ External references
 A good example of how to use the GPU CUDA driver library through the gpudev library
 is the l2fwd-nv application that can be found `here <https://github.com/NVIDIA/l2fwd-nv>`_.
 
-The application is based on vanilla DPDK example l2fwd
-and is enhanced with GPU memory managed through gpudev library
-and CUDA to launch the swap of packets MAC addresses workload on the GPU.
+The application is based on the DPDK example l2fwd,
+with GPU memory managed through gpudev library.
+It includes a CUDA workload swapping MAC addresses
+of packets received in the GPU.
 
 l2fwd-nv is not intended to be used for performance
 (testpmd is the good candidate for this).
-- 
2.25.1

---
  Diff of the applied patch vs upstream commit (please double-check if non-empty:
---
--- -	2023-08-09 21:51:21.182320200 +0800
+++ 0119-doc-improve-wording-of-cuda-guide.patch	2023-08-09 21:51:18.294352000 +0800
@@ -1 +1 @@
-From 135551ae0bae5a9e575b0a531490c24ef730dac0 Mon Sep 17 00:00:00 2001
+From fdb81fcc2ceb4cfd4271cd650c2cd3748e370cf7 Mon Sep 17 00:00:00 2001
@@ -4,0 +5,3 @@
+Cc: Xueming Li <xuemingl at nvidia.com>
+
+[ upstream commit 135551ae0bae5a9e575b0a531490c24ef730dac0 ]