Caffe* Training on Multi-node Distributed-memory Systems Based on Intel® Xeon® Processor E5 Family

Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and one of the most popular community frameworks for image recognition. Caffe is often used as a benchmark together with AlexNet*, a neural network topology for image recognition, and ImageNet*, a database of labeled images.
Автор: Gennady F. (Blackbelt) Последнее обновление: 05.07.2019 - 14:54

BigDL: Distributed Deep Learning on Apache Spark*

As the leading framework for Distributed ML, the addition of deep learning to the super-popular Spark framework is important, because it allows Spark developers to perform a wide range of data analysis tasks—including data wrangling, interactive queries, and stream processing—within a single framework. Three important features offered by BigDL are rich deep learning support, High Single Node Xeon...
Автор: Последнее обновление: 11.03.2019 - 13:17

BigDL – Scale-out Deep Learning on Apache Spark* Cluster

Learn how to install and use BigDL for training and testing some of the commonly used deep neural network models on Apache Spark.
Автор: Sunny G. (Intel) Последнее обновление: 11.03.2019 - 13:17