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| <div class="section" id="pyarrow-cuda-context"> |
| <h1>pyarrow.cuda.Context<a class="headerlink" href="#pyarrow-cuda-context" title="Permalink to this headline">¶</a></h1> |
| <dl class="py class"> |
| <dt id="pyarrow.cuda.Context"> |
| <em class="property">class </em><code class="sig-prename descclassname">pyarrow.cuda.</code><code class="sig-name descname">Context</code><a class="headerlink" href="#pyarrow.cuda.Context" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">pyarrow.lib._Weakrefable</span></code></p> |
| <p>CUDA driver context.</p> |
| <dl class="py method"> |
| <dt id="pyarrow.cuda.Context.__init__"> |
| <code class="sig-name descname">__init__</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.cuda.Context.__init__" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Create a CUDA driver context for a particular device.</p> |
| <p>If a CUDA context handle is passed, it is wrapped, otherwise |
| a default CUDA context for the given device is requested.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>device_number</strong> (<em>int</em><em> (</em><em>default 0</em><em>)</em>) – Specify the GPU device for which the CUDA driver context is |
| requested.</p></li> |
| <li><p><strong>handle</strong> (<em>int</em><em>, </em><em>optional</em>) – Specify CUDA handle for a shared context that has been created |
| by another library.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <p class="rubric">Methods</p> |
| <table class="longtable docutils align-default"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.__init__" title="pyarrow.cuda.Context.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a></p></td> |
| <td><p>Create a CUDA driver context for a particular device.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.buffer_from_data" title="pyarrow.cuda.Context.buffer_from_data"><code class="xref py py-obj docutils literal notranslate"><span class="pre">buffer_from_data</span></code></a></p></td> |
| <td><p>Create device buffer and initialize with data.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.buffer_from_object" title="pyarrow.cuda.Context.buffer_from_object"><code class="xref py py-obj docutils literal notranslate"><span class="pre">buffer_from_object</span></code></a></p></td> |
| <td><p>Create device buffer view of arbitrary object that references device accessible memory.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.foreign_buffer" title="pyarrow.cuda.Context.foreign_buffer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">foreign_buffer</span></code></a></p></td> |
| <td><p>Create device buffer from address and size as a view.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.from_numba" title="pyarrow.cuda.Context.from_numba"><code class="xref py py-obj docutils literal notranslate"><span class="pre">from_numba</span></code></a></p></td> |
| <td><p>Create a Context instance from a Numba CUDA context.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.get_device_address" title="pyarrow.cuda.Context.get_device_address"><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_device_address</span></code></a></p></td> |
| <td><p>Return the device address that is reachable from kernels running in the context</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.get_num_devices" title="pyarrow.cuda.Context.get_num_devices"><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_num_devices</span></code></a></p></td> |
| <td><p>Return the number of GPU devices.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.new_buffer" title="pyarrow.cuda.Context.new_buffer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">new_buffer</span></code></a></p></td> |
| <td><p>Return new device buffer.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.open_ipc_buffer" title="pyarrow.cuda.Context.open_ipc_buffer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">open_ipc_buffer</span></code></a></p></td> |
| <td><p>Open existing CUDA IPC memory handle</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.synchronize" title="pyarrow.cuda.Context.synchronize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">synchronize</span></code></a></p></td> |
| <td><p>Blocks until the device has completed all preceding requested tasks.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.to_numba" title="pyarrow.cuda.Context.to_numba"><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_numba</span></code></a></p></td> |
| <td><p>Convert Context to a Numba CUDA context.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Attributes</p> |
| <table class="longtable docutils align-default"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.bytes_allocated" title="pyarrow.cuda.Context.bytes_allocated"><code class="xref py py-obj docutils literal notranslate"><span class="pre">bytes_allocated</span></code></a></p></td> |
| <td><p>Return the number of allocated bytes.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.device_number" title="pyarrow.cuda.Context.device_number"><code class="xref py py-obj docutils literal notranslate"><span class="pre">device_number</span></code></a></p></td> |
| <td><p>Return context device number.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.cuda.Context.handle" title="pyarrow.cuda.Context.handle"><code class="xref py py-obj docutils literal notranslate"><span class="pre">handle</span></code></a></p></td> |
| <td><p>Return pointer to context handle.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <dl class="py method"> |
| <dt id="pyarrow.cuda.Context.buffer_from_data"> |
| <code class="sig-name descname">buffer_from_data</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.cuda.Context.buffer_from_data" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Create device buffer and initialize with data.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>data</strong> (<em>{CudaBuffer</em><em>, </em><a class="reference internal" href="pyarrow.cuda.HostBuffer.html#pyarrow.cuda.HostBuffer" title="pyarrow.cuda.HostBuffer"><em>HostBuffer</em></a><em>, </em><a class="reference internal" href="pyarrow.Buffer.html#pyarrow.Buffer" title="pyarrow.Buffer"><em>Buffer</em></a><em>, </em><em>array-like}</em>) – Specify data to be copied to device buffer.</p></li> |
| <li><p><strong>offset</strong> (<em>int</em>) – Specify the offset of input buffer for device data |
| buffering. Default: 0.</p></li> |
| <li><p><strong>size</strong> (<em>int</em>) – Specify the size of device buffer in bytes. Default: all |
| (starting from input offset)</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>cbuf</strong> (<em>CudaBuffer</em>) – Device buffer with copied data.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.cuda.Context.buffer_from_object"> |
| <code class="sig-name descname">buffer_from_object</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.cuda.Context.buffer_from_object" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Create device buffer view of arbitrary object that references |
| device accessible memory.</p> |
| <p>When the object contains a non-contiguous view of device |
| accessible memory then the returned device buffer will contain |
| contiguous view of the memory, that is, including the |
| intermediate data that is otherwise invisible to the input |
| object.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>obj</strong> (<em>{object</em><em>, </em><a class="reference internal" href="pyarrow.Buffer.html#pyarrow.Buffer" title="pyarrow.Buffer"><em>Buffer</em></a><em>, </em><a class="reference internal" href="pyarrow.cuda.HostBuffer.html#pyarrow.cuda.HostBuffer" title="pyarrow.cuda.HostBuffer"><em>HostBuffer</em></a><em>, </em><a class="reference internal" href="pyarrow.cuda.CudaBuffer.html#pyarrow.cuda.CudaBuffer" title="pyarrow.cuda.CudaBuffer"><em>CudaBuffer</em></a><em>, </em><em>..}</em>) – Specify an object that holds (device or host) address that |
| can be accessed from device. This includes objects with |
| types defined in pyarrow.cuda as well as arbitrary objects |
| that implement the CUDA array interface as defined by numba.</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>cbuf</strong> (<em>CudaBuffer</em>) – Device buffer as a view of device accessible memory.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyarrow.cuda.Context.bytes_allocated"> |
| <code class="sig-name descname">bytes_allocated</code><a class="headerlink" href="#pyarrow.cuda.Context.bytes_allocated" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Return the number of allocated bytes.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyarrow.cuda.Context.device_number"> |
| <code class="sig-name descname">device_number</code><a class="headerlink" href="#pyarrow.cuda.Context.device_number" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Return context device number.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.cuda.Context.foreign_buffer"> |
| <code class="sig-name descname">foreign_buffer</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.cuda.Context.foreign_buffer" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Create device buffer from address and size as a view.</p> |
| <p>The caller is responsible for allocating and freeing the |
| memory. When <cite>address==size==0</cite> then a new zero-sized buffer |
| is returned.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>address</strong> (<em>int</em>) – Specify the starting address of the buffer. The address can |
| refer to both device or host memory but it must be |
| accessible from device after mapping it with |
| <cite>get_device_address</cite> method.</p></li> |
| <li><p><strong>size</strong> (<em>int</em>) – Specify the size of device buffer in bytes.</p></li> |
| <li><p><strong>base</strong> (<em>{None</em><em>, </em><em>object}</em>) – Specify object that owns the referenced memory.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>cbuf</strong> (<em>CudaBuffer</em>) – Device buffer as a view of device reachable memory.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.cuda.Context.from_numba"> |
| <em class="property">static </em><code class="sig-name descname">from_numba</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.cuda.Context.from_numba" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Create a Context instance from a Numba CUDA context.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>context</strong> (<em>{numba.cuda.cudadrv.driver.Context</em><em>, </em><em>None}</em>) – A Numba CUDA context instance. |
| If None, the current Numba context is used.</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>shared_context</strong> (<em>pyarrow.cuda.Context</em>) – Context instance.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.cuda.Context.get_device_address"> |
| <code class="sig-name descname">get_device_address</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.cuda.Context.get_device_address" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Return the device address that is reachable from kernels running in |
| the context</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>address</strong> (<em>int</em>) – Specify memory address value</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>device_address</strong> (<em>int</em>) – Device address accessible from device context</p> |
| </dd> |
| </dl> |
| <p class="rubric">Notes</p> |
| <p>The device address is defined as a memory address accessible |
| by device. While it is often a device memory address but it |
| can be also a host memory address, for instance, when the |
| memory is allocated as host memory (using cudaMallocHost or |
| cudaHostAlloc) or as managed memory (using cudaMallocManaged) |
| or the host memory is page-locked (using cudaHostRegister).</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.cuda.Context.get_num_devices"> |
| <em class="property">static </em><code class="sig-name descname">get_num_devices</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.cuda.Context.get_num_devices" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Return the number of GPU devices.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyarrow.cuda.Context.handle"> |
| <code class="sig-name descname">handle</code><a class="headerlink" href="#pyarrow.cuda.Context.handle" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Return pointer to context handle.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.cuda.Context.new_buffer"> |
| <code class="sig-name descname">new_buffer</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.cuda.Context.new_buffer" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Return new device buffer.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>nbytes</strong> (<em>int</em>) – Specify the number of bytes to be allocated.</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>buf</strong> (<em>CudaBuffer</em>) – Allocated buffer.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.cuda.Context.open_ipc_buffer"> |
| <code class="sig-name descname">open_ipc_buffer</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.cuda.Context.open_ipc_buffer" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Open existing CUDA IPC memory handle</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>ipc_handle</strong> (<a class="reference internal" href="pyarrow.cuda.IpcMemHandle.html#pyarrow.cuda.IpcMemHandle" title="pyarrow.cuda.IpcMemHandle"><em>IpcMemHandle</em></a>) – Specify opaque pointer to CUipcMemHandle (driver API).</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>buf</strong> (<em>CudaBuffer</em>) – referencing device buffer</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.cuda.Context.synchronize"> |
| <code class="sig-name descname">synchronize</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.cuda.Context.synchronize" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Blocks until the device has completed all preceding requested |
| tasks.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.cuda.Context.to_numba"> |
| <code class="sig-name descname">to_numba</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.cuda.Context.to_numba" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Convert Context to a Numba CUDA context.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Returns</dt> |
| <dd class="field-odd"><p><strong>context</strong> (<em>numba.cuda.cudadrv.driver.Context</em>) – Numba CUDA context instance.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| </dd></dl> |
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