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    <title>topic Re: Train Deep Learning Model Using Multiple GPUs on Windows machine in ArcGIS Pro Questions</title>
    <link>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1221252#M60977</link>
    <description>&lt;P&gt;Yes.&amp;nbsp; The deep learning library has Environment parameters that allow you to specify processor type.&amp;nbsp; But it only has one slot for GPU processor.&amp;nbsp; I'm wondering if you can place comma for each ID, like in python.&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Wed, 12 Oct 2022 19:42:34 GMT</pubDate>
    <dc:creator>JadedEarth</dc:creator>
    <dc:date>2022-10-12T19:42:34Z</dc:date>
    <item>
      <title>Train Deep Learning Model Using Multiple GPUs on Windows machine</title>
      <link>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1221102#M60954</link>
      <description>&lt;P&gt;I'm using ArcGIS Pro version 2.9.&amp;nbsp; We have installed 6 GPUs in one machine but when I train deep learning model, there is no space to specify the IDs of the GPUs; only one space is available.&amp;nbsp; However, it seems to randomly select which GPU it uses.&amp;nbsp; Is this normal?&lt;/P&gt;&lt;P&gt;I'm not using Python.&amp;nbsp; I'm just using Image Analyst to run the deep learning.&lt;/P&gt;&lt;P&gt;Any help is appreciated.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 12 Oct 2022 14:14:03 GMT</pubDate>
      <guid>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1221102#M60954</guid>
      <dc:creator>JadedEarth</dc:creator>
      <dc:date>2022-10-12T14:14:03Z</dc:date>
    </item>
    <item>
      <title>Re: Train Deep Learning Model Using Multiple GPUs on Windows machine</title>
      <link>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1221156#M60962</link>
      <description>&lt;P&gt;&lt;A href="https://pro.arcgis.com/en/pro-app/latest/tool-reference/environment-settings/gpu-id.htm" target="_blank"&gt;GPU ID (Environment setting)—ArcGIS Pro | Documentation&lt;/A&gt;&lt;/P&gt;&lt;P&gt;does the tool you are using support the GPU environment setting?&lt;/P&gt;</description>
      <pubDate>Wed, 12 Oct 2022 15:58:17 GMT</pubDate>
      <guid>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1221156#M60962</guid>
      <dc:creator>DanPatterson</dc:creator>
      <dc:date>2022-10-12T15:58:17Z</dc:date>
    </item>
    <item>
      <title>Re: Train Deep Learning Model Using Multiple GPUs on Windows machine</title>
      <link>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1221252#M60977</link>
      <description>&lt;P&gt;Yes.&amp;nbsp; The deep learning library has Environment parameters that allow you to specify processor type.&amp;nbsp; But it only has one slot for GPU processor.&amp;nbsp; I'm wondering if you can place comma for each ID, like in python.&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 12 Oct 2022 19:42:34 GMT</pubDate>
      <guid>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1221252#M60977</guid>
      <dc:creator>JadedEarth</dc:creator>
      <dc:date>2022-10-12T19:42:34Z</dc:date>
    </item>
    <item>
      <title>Re: Train Deep Learning Model Using Multiple GPUs on Windows machine</title>
      <link>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1221582#M61021</link>
      <description>&lt;P&gt;Since I can't get this to work in Image Analyst, I'm switching to arcgis.learn using Jupyter Notebook interface in ArcGIS Pro.&lt;/P&gt;&lt;P&gt;Does anybody have sample Python codes to train model using multiple GPUs and using Data Parallelism?&lt;/P&gt;</description>
      <pubDate>Thu, 13 Oct 2022 15:13:11 GMT</pubDate>
      <guid>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1221582#M61021</guid>
      <dc:creator>JadedEarth</dc:creator>
      <dc:date>2022-10-13T15:13:11Z</dc:date>
    </item>
    <item>
      <title>Re: Train Deep Learning Model Using Multiple GPUs on Windows machine</title>
      <link>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1221994#M61083</link>
      <description>&lt;P&gt;Further research:&amp;nbsp; I really need to use Python codes for now; not only that, I need to use distributed data parallelism to be able to use multiple GPUs.&amp;nbsp; This seems to be quite complicated.&amp;nbsp; I'm still researching and will test whatever I find in literature.&amp;nbsp; This is not a solution but I'll end this thread here.&lt;/P&gt;</description>
      <pubDate>Fri, 14 Oct 2022 13:00:20 GMT</pubDate>
      <guid>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1221994#M61083</guid>
      <dc:creator>JadedEarth</dc:creator>
      <dc:date>2022-10-14T13:00:20Z</dc:date>
    </item>
    <item>
      <title>Re: Train Deep Learning Model Using Multiple GPUs on Windows machine</title>
      <link>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1264477#M66277</link>
      <description>&lt;P&gt;&lt;a href="https://community.esri.com/t5/user/viewprofilepage/user-id/551486"&gt;@JadedEarth&lt;/a&gt;&amp;nbsp;did you see the sample code here? I'm not sure when it was posted relative to your question, but I believe it was available last year:&amp;nbsp;&lt;A href="https://developers.arcgis.com/python/guide/utilize-multiple-gpus-to-train-model/" target="_blank"&gt;Train arcgis.learn models on multiple GPUs | ArcGIS API for Python&lt;/A&gt;&lt;/P&gt;</description>
      <pubDate>Mon, 06 Mar 2023 14:35:28 GMT</pubDate>
      <guid>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1264477#M66277</guid>
      <dc:creator>JeffreyHolycross</dc:creator>
      <dc:date>2023-03-06T14:35:28Z</dc:date>
    </item>
    <item>
      <title>Re: Train Deep Learning Model Using Multiple GPUs on Windows machine</title>
      <link>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1331652#M73349</link>
      <description>&lt;P&gt;&lt;a href="https://community.esri.com/t5/user/viewprofilepage/user-id/551486"&gt;@JadedEarth&lt;/a&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;At upcoming v3.2, b&lt;SPAN&gt;y default, the Train Deep Learning tool is planned to use all available GPUs on a single machine when the&lt;/SPAN&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN class=""&gt;Model Type&lt;/SPAN&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN&gt;&amp;nbsp;is set to one of the following:&lt;/SPAN&gt;&lt;/P&gt;&lt;UL&gt;&lt;LI&gt;&lt;UL&gt;&lt;LI&gt;&lt;SPAN class=""&gt;ConnectNet&lt;/SPAN&gt;&lt;/LI&gt;&lt;LI&gt;&lt;SPAN class=""&gt;Feature classifier&lt;/SPAN&gt;&lt;/LI&gt;&lt;LI&gt;&lt;SPAN class=""&gt;MaskRCNN&lt;/SPAN&gt;&lt;/LI&gt;&lt;LI&gt;&lt;SPAN class=""&gt;Multi Task Road Extractor&lt;/SPAN&gt;&lt;/LI&gt;&lt;LI&gt;&lt;SPAN class=""&gt;Single Shot Detector&lt;/SPAN&gt;&lt;/LI&gt;&lt;LI&gt;&lt;SPAN class=""&gt;U-Net&lt;/SPAN&gt;&lt;/LI&gt;&lt;/UL&gt;&lt;P&gt;To use a specific GPU, you can use the GPU ID environment.&lt;/P&gt;between 2.8 and 3.1, the tool could use multiple GPUs by default but the feature was not certified and thus not documented.&amp;nbsp;&lt;/LI&gt;&lt;/UL&gt;&lt;P&gt;You could&amp;nbsp; use API:&amp;nbsp;&lt;A href="https://developers.arcgis.com/python/guide/utilize-multiple-gpus-to-train-model/" target="_blank" rel="noopener"&gt;https://developers.arcgis.com/python/guide/utilize-multiple-gpus-to-train-model/&lt;/A&gt;&amp;nbsp;if ArcGIS Pro's current support does not meet your need.&amp;nbsp;&lt;/P&gt;&lt;P&gt;We hope to support multiple GPUs on single machine for inferencing as well in upcoming releases.&amp;nbsp;&lt;BR /&gt;&lt;BR /&gt;&lt;SPAN&gt;A side note: We have an&amp;nbsp;&lt;A href="https://community.esri.com/t5/arcgis-image-analyst/ct-p/arcgis-image-analyst" target="_blank" rel="noopener"&gt;ArcGIS Image Analyst&lt;/A&gt;&amp;nbsp;dedicated community and here you might get response sooner.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Cheers!&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Pavan Yadav | Product Engineer - Imagery and AI&lt;BR /&gt;Esri | 380 New York | Redlands, 92373 | USA&lt;BR /&gt;&lt;BR /&gt;&lt;A href="https://www.linkedin.com/in/pavan-yadav-1846606/" target="_blank" rel="noopener"&gt;https://www.linkedin.com/in/pavan-yadav-1846606/&lt;/A&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;</description>
      <pubDate>Fri, 22 Sep 2023 20:31:09 GMT</pubDate>
      <guid>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1331652#M73349</guid>
      <dc:creator>PavanYadav</dc:creator>
      <dc:date>2023-09-22T20:31:09Z</dc:date>
    </item>
    <item>
      <title>Re: Train Deep Learning Model Using Multiple GPUs on Windows machine</title>
      <link>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1343820#M74672</link>
      <description>&lt;P&gt;I need the HED edge detection model.&amp;nbsp; This is the only one that works with field boundary extraction.&amp;nbsp; Is this not going to be included in this update?&amp;nbsp; If not, then I'm still out of luck.&amp;nbsp; I've tried all the other models you mentioned for my work but only HED model comes up with reasonable (not perfect) results.&lt;/P&gt;&lt;P&gt;I do hope you include HED among the multiple GPU supports since both USDA and EPA really need this.&lt;/P&gt;&lt;P&gt;I appreciate your assistance.&lt;/P&gt;</description>
      <pubDate>Tue, 31 Oct 2023 14:00:58 GMT</pubDate>
      <guid>https://community.esri.com/t5/arcgis-pro-questions/train-deep-learning-model-using-multiple-gpus-on/m-p/1343820#M74672</guid>
      <dc:creator>JadedEarth</dc:creator>
      <dc:date>2023-10-31T14:00:58Z</dc:date>
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