{"title":"PyVideo.org - APEX","link":[{"@attributes":{"href":"https:\/\/pyvideo.org\/","rel":"alternate"}},{"@attributes":{"href":"https:\/\/pyvideo.org\/feeds\/tag_apex.atom.xml","rel":"self"}}],"id":"https:\/\/pyvideo.org\/","updated":"2019-10-16T00:00:00+00:00","subtitle":{},"entry":{"title":"Apex","link":{"@attributes":{"href":"https:\/\/pyvideo.org\/pytorch-conference-2019\/apex.html","rel":"alternate"}},"published":"2019-10-16T00:00:00+00:00","updated":"2019-10-16T00:00:00+00:00","author":{"name":"Michael Carilli"},"id":"tag:pyvideo.org,2019-10-16:\/pytorch-conference-2019\/apex.html","content":"<h3>Description<\/h3><p>Apex is an open-source PyTorch extension that helps users maximize deep learning training performance on NVIDIA GPUs. Mixed precision utilities in Apex are designed to improve training speed while maintaining the accuracy and stability of training in single precision. Learn more in this talk.<\/p>\n","category":[{"@attributes":{"term":"PyTorch Conference 2019"}},{"@attributes":{"term":"AI"}},{"@attributes":{"term":"APEX"}},{"@attributes":{"term":"Artificial Intelligence"}},{"@attributes":{"term":"Deep Learning"}},{"@attributes":{"term":"Distributed Training"}},{"@attributes":{"term":"Facebook"}},{"@attributes":{"term":"ML"}},{"@attributes":{"term":"Machine Learning"}},{"@attributes":{"term":"Mixed Precision"}},{"@attributes":{"term":"NVIDIA"}},{"@attributes":{"term":"NVIDIA GPU"}},{"@attributes":{"term":"PyTorch"}},{"@attributes":{"term":"PyTorch 1.3"}}]}}