Introduction
In 2017, we introduced Horovod, an open source framework for scaling deep learning training across hundreds of GPUs in parallel. At the time, most of the deep learning use cases at Uber were related to the research and …
In 2017, we introduced Horovod, an open source framework for scaling deep learning training across hundreds of GPUs in parallel. At the time, most of the deep learning use cases at Uber were related to the research and …
We originally open-sourced Horovod in 2017, and since then it has grown to become the standard solution in industry for scaling deep learning training to hundreds of GPUs. With Horovod, you can reduce training times from days or weeks to …
In February 2019, Uber released Ludwig, an open source, code-free deep learning (DL) toolbox that gives non-programmers and advanced machine learning (ML) practitioners alike the power to develop models for a variety of DL tasks. With use cases spanning text …