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<p>Device dùng ở đây nghĩa là thiết bị phần cứng với bộ nhớ và các bộ phận máy
tính. Tất cả <a href="./tensor">Tensor operations</a> được sắp xếp bởi các thiết bị
resident device khi chạy. Bộ nhớ của Tensor luôn luôn được quản lý bởi memory
manager của thiết bị đó. Bởi vậy việc tận dụng tối đa bộ nhớ và thực hiện được
tiến hành tại Device class.</p>
<h2><a class="anchor" aria-hidden="true" id="các-thiết-bị-cụ-thể"></a><a href="#các-thiết-bị-cụ-thể" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Các thiết bị cụ thể</h2>
<p>Hiện tại, SINGA được chạy trên ba Device,</p>
<ol>
<li>CudaGPU cho cạc Nvidia GPU card chạy code Cuda</li>
<li>CppCPU cho CPU chạy Cpp code</li>
<li>OpenclGPU cho cạc GPU chạy OpenCL code</li>
</ol>
<h2><a class="anchor" aria-hidden="true" id="ví-dụ-sử-dụng"></a><a href="#ví-dụ-sử-dụng" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Ví Dụ Sử Dụng</h2>
<p>Code dưới đây là ví dụ về việc tạo device:</p>
<pre><code class="hljs css language-python"><span class="hljs-keyword">from</span> singa <span class="hljs-keyword">import</span> device
cuda = device.create_cuda_gpu_on(<span class="hljs-number">0</span>) <span class="hljs-comment"># sử dụng cạc GPU với ID 0</span>
host = device.get_default_device() <span class="hljs-comment"># tạo host mặc định cho device (CppCPU)</span>
ary1 = device.create_cuda_gpus(<span class="hljs-number">2</span>) <span class="hljs-comment"># tạo 2 devices, bắt đầu từ ID 0</span>
ary2 = device.create_cuda_gpus([<span class="hljs-number">0</span>,<span class="hljs-number">2</span>]) <span class="hljs-comment"># tạo 2 devices với ID 0 và 2</span>
</code></pre>
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