Uber’s open-source distributed training framework Horovod is joining the LF Deep Learning Foundation to support its work in artificial intelligence, machine learning and deep learning. The LF Deep Learning Foundation is a umbrella project under the Linux Foundation.
“The LF Deep Learning Foundation is focused on building an ecosystem of AI, deep learning and machine learning projects. Today’s announcement of Uber’s contribution of the Horovod project represents significant progress toward achieving this vision,” said Ibrahim Haddad, Linux Foundation director of research. “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.”
Horovod is designed for other deep learning projects like TensorFlow, Keras and PyTorch. The goal of the project is to make distributed deep learning fast and easier to use. The primary goal of the project was to take a single-GPU TensorFlow program and train it on GPUs faster. According to the foundation, Horovod has been able to improve GPU resource usage figures with advance algorithms and high-performance networks. Uber also explained that the project scales significantly better than standard distributed TensorFlow, and is twice as first.
Uber has been using Horovod for self-driving vehicles, fraud detection, and trip forecasting. It has also be used by other industry leaders such as Alibaba, Amazon and NVIDIA.
“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 as the LF Deep Learning Foundation’s newest project. As Horovod continues to mature in its functionalities and applications, this collaboration will enable us to further scale its impact in the open source ecosystem for the advancement of AI.”
