Docs for pull request 1731

Author: github-actions[doc-deploy-bot]

pulls/1731/_sources/beginners_guides/installation.rst.txt

@@ -158,12 +158,28 @@ The following plugins from CodePlay are supported:
 .. _codeplay_nv_plugin: https://developer.codeplay.com/products/oneapi/nvidia/
 .. _codeplay_amd_plugin: https://developer.codeplay.com/products/oneapi/amd/
 
-Build ``dpctl`` as follows:
+``dpctl`` can be built for CUDA devices as follows:
 
 .. code-block:: bash
 
     python scripts/build_locally.py --verbose --cmake-opts="-DDPCTL_TARGET_CUDA=ON"
 
+And for AMD devices
+
+.. code-block:: bash
+
+    python scripts/build_locally.py --verbose --cmake-opts="-DDPCTL_TARGET_HIP=gfx1030"
+
+Note that the  `oneAPI for AMD GPUs <codeplay_amd_plugin_>` plugin requires the architecture
+be specified and only one architecture can be specified at a time.
+
+It is, however, possible to build for Intel devices, CUDA devices, and an AMD device
+architecture all at once:
+
+.. code-block:: bash
+
+    python scripts/build_locally.py --verbose --cmake-opts="-DDPCTL_TARGET_CUDA=ON \
+    -DDPCTL_TARGET_HIP=gfx1030"
 
 Running Examples and Tests
 ==========================

pulls/1731/_sources/beginners_guides/managing_devices.rst.txt

@@ -123,6 +123,9 @@ of valid settings are:
     * - ``cuda:*``
       - All devices only from CUDA backend are available
 
+    * - ``hip:*``
+      - All devices only from HIP backend are available
+
     * - ``level_zero:0,1``
       - Two specific devices from Level-Zero backend are available
 

pulls/1731/beginners_guides/installation.html

@@ -881,7 +881,7 @@ <h2>Installation using pip<a class="headerlink" href="#installation-using-pip" t
 <section id="installation-via-intel-r-distribution-for-python">
 <h2>Installation via Intel(R) Distribution for Python<a class="headerlink" href="#installation-via-intel-r-distribution-for-python" title="Permalink to this heading">¶</a></h2>
 <p><a class="reference external" href="https://www.intel.com/content/www/us/en/developer/tools/oneapi/distribution-for-python.html">Intel(R) Distribution for Python*</a> is distributed as a conda-based installer
-and includes <a class="reference internal" href="../api_reference/dpctl/index.html#module-dpctl" title="dpctl"><code class="xref py py-mod docutils literal notranslate"><span class="pre">dpctl</span></code></a> along with its dependencies and sister projects <a class="reference external" href="https://intelpython.github.io/dpnp/overview.html#module-dpnp" title="(in Data Parallel Extension for NumPy v0.17.0dev2+12.gffd3829f601)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">dpnp</span></code></a>
+and includes <a class="reference internal" href="../api_reference/dpctl/index.html#module-dpctl" title="dpctl"><code class="xref py py-mod docutils literal notranslate"><span class="pre">dpctl</span></code></a> along with its dependencies and sister projects <a class="reference external" href="https://intelpython.github.io/dpnp/overview.html#module-dpnp" title="(in Data Parallel Extension for NumPy v0.17.0dev2+14.g1c375af39b0)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">dpnp</span></code></a>
 and <a class="reference external" href="https://intelpython.github.io/numba-dpex/latest/index.html#module-numba_dpex" title="(in numba-dpex)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">numba_dpex</span></code></a>.</p>
 <p>Once the installed environment is activated, <code class="docutils literal notranslate"><span class="pre">dpctl</span></code> should be ready to use.</p>
 </section>
@@ -946,10 +946,22 @@ <h3>Building for custom SYCL targets<a class="headerlink" href="#building-for-cu
 <li><p><a class="reference external" href="https://developer.codeplay.com/products/oneapi/amd/">oneAPI for AMD GPUs</a></p></li>
 </ul>
 </div></blockquote>
-<p>Build <code class="docutils literal notranslate"><span class="pre">dpctl</span></code> as follows:</p>
+<p><code class="docutils literal notranslate"><span class="pre">dpctl</span></code> can be built for CUDA devices as follows:</p>
 <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>scripts/build_locally.py<span class="w"> </span>--verbose<span class="w"> </span>--cmake-opts<span class="o">=</span><span class="s2">&quot;-DDPCTL_TARGET_CUDA=ON&quot;</span>
 </pre></div>
 </div>
+<p>And for AMD devices</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>scripts/build_locally.py<span class="w"> </span>--verbose<span class="w"> </span>--cmake-opts<span class="o">=</span><span class="s2">&quot;-DDPCTL_TARGET_HIP=gfx1030&quot;</span>
+</pre></div>
+</div>
+<p>Note that the  <cite>oneAPI for AMD GPUs &lt;codeplay_amd_plugin_&gt;</cite> plugin requires the architecture
+be specified and only one architecture can be specified at a time.</p>
+<p>It is, however, possible to build for Intel devices, CUDA devices, and an AMD device
+architecture all at once:</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>scripts/build_locally.py<span class="w"> </span>--verbose<span class="w"> </span>--cmake-opts<span class="o">=</span><span class="s2">&quot;-DDPCTL_TARGET_CUDA=ON \</span>
+<span class="s2">-DDPCTL_TARGET_HIP=gfx1030&quot;</span>
+</pre></div>
+</div>
 </section>
 </section>
 <section id="running-examples-and-tests">

pulls/1731/beginners_guides/managing_devices.html

@@ -928,10 +928,13 @@ <h3>Listing devices programmatically<a class="headerlink" href="#listing-devices
 <tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">cuda:*</span></code></p></td>
 <td><p>All devices only from CUDA backend are available</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">level_zero:0,1</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">hip:*</span></code></p></td>
+<td><p>All devices only from HIP backend are available</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">level_zero:0,1</span></code></p></td>
 <td><p>Two specific devices from Level-Zero backend are available</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">level_zero:gpu;cuda:gpu;opencl:cpu</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">level_zero:gpu;cuda:gpu;opencl:cpu</span></code></p></td>
 <td><p>Level-Zero GPU devices, CUDA GPU devices, and OpenCL CPU devices are available</p></td>
 </tr>
 </tbody>