LF Deep Learning takes on Angel and EDL Projects

August 27, 2018

Press Release

LF Deep Learning takes on Angel and EDL Projects

With these two new projects, the Foundation adds technology finely tuned for big data and deep learning via clusters with Baidu?s PaddlePaddle and Kubernetes container orchestration.

The LF Deep Learning Foundation announced it will be accepting two additional projects into its foundation: the Angel Project and the EDL Project, in an effort to build an ecosystem of AI, deep learning and machine learning projects.

With these two new projects, the Foundation adds technology finely tuned for big data and deep learning via clusters with Baidu’s PaddlePaddle and Kubernetes container orchestration.

Angel Project Background

The Angel Project is a high-performance distributed machine learning platform based on Parameter Server, running on YARN and Apache Spark.

The system is designed for efficient iteration computation, so that machine learning algorithms can benefit from it. Algorithms in Angel are out-of-the-box, so analysts and data scientists can submit jobs without writing a single line code.

“Angel shares a common goal with the LF Deep Learning Foundation: to make deep learning easier to use. By becoming a part of the LF Deep Learning Foundation, we believe Angel will be more active in the open source community, accumulate more use cases, expand usage scenarios and actively cooperate with other partners,” said Xiaolong Zhu, Tencent senior AI researcher and TAC member of the LF Deep Learning Foundation. “As a new project under the Foundation, Angel will continue working on a consistent and continuous user experience to make deep learning technology easier to apply and develop.”

EDL Project Background

EDL is an Elastic Deep Learning framework designed to help deep learning cloud service providers to build cluster cloud services using deep learning frameworks such as PaddlePaddle and TensorFlow.

EDL includes a Kubernetes controller, PaddlePaddle auto-scaler, which changes the number of processes of distributed jobs to the idle hardware resource in the cluster, and a new fault-tolerable architecture.

"We are excited to see that EDL has been accepted to LF Deep Learning Foundation,” said Yanjun Ma, Head of Deep Learning Technology Department, Baidu. “As an elastic deep learning framework for PaddlePaddle, we believe that EDL will substantially benefit the deployment of large-scale deep learning services, and the broader deep learning open source community.”

Organizations interested in contributing projects and learning more about LF Deep Learning Foundation, visit www.deeplearningfoundation.org.

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