Announced today, Horovod, Uber’s open source distributed training framework, joins the LF Deep Learning Foundation, a community umbrella project of The Linux Foundation that supports and sustains open source innovation in artificial intelligence, machine learning, and deep learning.

“The LF Deep Learning Foundation is focused on building an ecosystem of AI, deep learning and machine learning projects, and today’s announcement of Uber’s contribution of the Horovod project to the foundation represents significant progress toward achieving this vision,” said Linux Foundation Director of Research Ibrahim Haddad. “This project has proven highly effective in training machine learning models quickly and efficiently, and we look forward to working to further grow the Horovod community and encourage adoption of this exciting project.”

Released by Uber under the open source Apache 2.0 license in October 2017, Horovod makes it faster and easier for AI practitioners to train distributed deep learning models with TensorFlow, Keras, and PyTorch. Services such as AWS Deep Learning AMI, Azure Data Science VM, Databricks Runtime, GCP Deep Learning VM, IBM FfDL, IBM Watson Studio, and NVIDIA GPU Cloud integrate Horovod, making it readily available to companies and organizations looking to leverage deep learning. In 2018, InfoWorld named Horovod one of the best open source software projects in machine learning.

“Uber built Horovod to make deep learning model training faster and more intuitive for AI researchers across industries,” said Alex Sergeev, Horovod Project Lead. “In this spirit, we are honored to contribute Horovod to the deep learning community through its incorporation as the LF Deep Learning Foundation’s newest project. As Horovod continues to mature in its functionalities and applications, being an LF Deep Learning Foundation project will enable us to further scale its impact across the open source ecosystem for the advancement of AI.”

 

For more information about this news, check out the LF Deep Learning Foundation’s official announcement and read our Q&A with Alex Sergeev, Horovod Project Lead, about his journey to Horovod and open source at Uber.