I created a new JIRA entry https://issues.apache.org/jira/browse/SPARK-12620 for this instead of reopening the existing JIRA based on the suggestion.
Best Regards, Kazuaki Ishizaki From: Kazuaki Ishizaki/Japan/IBM@IBMJP To: dev@spark.apache.org Date: 2016/01/04 12:54 Subject: Support off-loading computations to a GPU Dear all, We reopened the existing JIRA entry https://issues.apache.org/jira/browse/SPARK-3785to support off-loading computations to a GPU by adding a description for our prototype. We are working to effectively and easily exploit GPUs on Spark at http://github.com/kiszk/spark-gpu. Please also visit our project page http://kiszk.github.io/spark-gpu/. For now, we added a new format for a partition in an RDD, which is a column-based structure in an array format, in addition to the current Iterator[T] format with Seq[T]. This reduces data serialization/deserialization and copy overhead between CPU and GPU. Our prototype achieved more than 3x performance improvement for a simple logistic regression program using a NVIDIA K40 card. This JIRA entry (SPARK-3785) includes a link to a design document. We are very glad to hear valuable feedback/suggestions/comments and to have great discussions to exploit GPUs in Spark. Best Regards, Kazuaki Ishizaki
