Announcing Single-Node Clusters on Databricks
Databricks is used by data teams to solve the world's toughest problems. This can involve running large-scale data processing jobs to extract, transform, and analyze data. However, it often also involves data analysis, data science, and machine learning at the scale of a single machine, for instance using libraries like scikit-learn. To streamline these single...
Announcing GPU-aware scheduling and enhanced deep learning capabilities
Databricks is pleased to announce the release of Databricks Runtime 7.0 for Machine Learning (Runtime 7.0 ML) which provides preconfigured GPU-aware scheduling and adds enhanced deep learning capabilities for training and inference workloads. Preconfigured GPU-aware scheduling Project Hydrogen is a major Apache Spark™ initiative to bring state-of-the-art artificial intelligence (AI) and Big Data solutions together....
Introducing HorovodRunner for Distributed Deep Learning Training
Today, we are excited to introduce HorovodRunner in our Databricks Runtime 5.0 ML! HorovodRunner provides a simple way to scale up your deep learning training workloads from a single machine to large clusters, reducing overall training time. Motivated by the needs of many of our users who want to train deep learning models on datasets...
