[ https://issues.apache.org/jira/browse/SPARK-22658?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-22658. ---------------------------------- Resolution: Incomplete > SPIP: TeansorFlowOnSpark as a Scalable Deep Learning Lib of Apache Spark > ------------------------------------------------------------------------ > > Key: SPARK-22658 > URL: https://issues.apache.org/jira/browse/SPARK-22658 > Project: Spark > Issue Type: New Feature > Components: ML > Affects Versions: 2.2.0 > Reporter: Andy Feng > Priority: Major > Labels: bulk-closed > Attachments: SPIP_ TensorFlowOnSpark.pdf > > Original Estimate: 336h > Remaining Estimate: 336h > > TensorFlowOnSpark (TFoS) was released at github for distributed TensorFlow > training and inference on Apache Spark clusters. TFoS is designed to: > * Easily migrate all existing TensorFlow programs with minimum code change; > * Support all TensorFlow functionalities: synchronous/asynchronous training, > model/data parallelism, inference and TensorBoard; > * Easily integrate with your existing data processing pipelines (ex. Spark > SQL) and machine learning algorithms (ex. MLlib); > * Be easily deployed on cloud or on-premise: CPU & GPU, Ethernet and > Infiniband. > We propose to merge TFoS into Apache Spark as a scalable deep learning > library to: > * Make deep learning easy for Apache Spark community: Familiar pipeline API > for training and inference; Enable TensorFlow training/inference on existing > Spark clusters. > * Further simplify data scientist experience: Ensure compatibility b/w Apache > Spark and TFoS; Reduce steps for installation. > * Help Apache Spark evolutions on deep learning: Establish a design pattern > for additional frameworks (ex. Caffe, CNTK); Structured streaming for DL > training/inference. -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org