<p dir="auto">Many projects require more resources than are available in a single machine. <strong>Does the current opensource release of Tensorflow support processing that spans multiple-machines?</strong></p>
<p dir="auto">I ask because the main webpage (says single machine) seems to conflict[1] with the Tensorflow whitepaper pdf (says multiple machines).</p>
<p dir="auto">If the current opensource tensorflow does not support multiple-machine execution but the closed-sourced version does. <strong>Is there any plan to release an opensource version that supports multiple machines? Is there an approximate timeframe?</strong></p>
<p dir="auto">[1]</p>
<ul dir="auto">
<li>The <a href="http://tensorflow.org/" rel="nofollow">tensorflow.org main webpage</a> says "This open source release supports single machines". Also the <a href="http://tensorflow.org/resources/faq.md" rel="nofollow">Resources/FAQ says "single computer"</a>.</li>
<li>But then when you <a href="http://download.tensorflow.org/paper/whitepaper2015.pdf" rel="nofollow">read the Tensorflow whitepaper</a>, the whitepaper indicates in many places that Tensorflow can run across multiple machines. See these quotes from the whitepaper:
<ul dir="auto">
<li>"large-scale  distributed  systems  of  hundreds of machines" and "using<br>
many  hundreds  of  machines"</li>
<li>" extends  it with  support  for  an environment where the client, the master, and the workers can all be in different processes on different machines"</li>
<li>"use remote communication mechanisms such as TCP or RDMA to move data across machine boundaries"</li>
</ul>
</li>
</ul>
<p dir="auto">Is there any distributed version of TensorFlow that could work on multiple machines?</p>
<p dir="auto">-Minjie</p>