Databricks Adds Deep Learning Support to Cloud-Based Apache Spark Platform

Databricks, the company founded by the creators of the Apache Spark project, has added deep learning support to its cloud-based Apache Spark platform.

This enhancement adds GPU support and integrates popular deep learning libraries to the Databricks' big data platform, extending its capabilities to enable the rapid development of deep learning models.

In March 2016, Databricks created and open sourced TensorFrames, a software library that enables the deep learning framework, TensorFlow to run on Spark. According to the company, the new Databricks enhancements simplify deep learning on Spark by adding out-of-the-box support for using TensorFrames with GPUs - specialized hardware that can perform deep learning-specific computations in parallel.

By combining techniques such as data wrangling, interactive exploration, stream data processing, as well as other advanced analytics, on Databricks, the company says organizations can avoid unwanted system complexities and streamline the development of deep learning applications for better medical care, drug discovery, and artificial intelligence use cases, such as language translation.

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