Uploaded image for project: 'Spark'
  1. Spark
  2. SPARK-1485

Implement AllReduce

Log workAgile BoardRank to TopRank to BottomAttach filesAttach ScreenshotVotersStop watchingWatchersCreate sub-taskConvert to sub-taskLinkCloneLabelsUpdate Comment AuthorReplace String in CommentUpdate Comment VisibilityDelete Comments
    XMLWordPrintableJSON

    Details

    • Type: Improvement
    • Status: Resolved
    • Priority: Critical
    • Resolution: Won't Fix
    • Affects Version/s: None
    • Fix Version/s: None
    • Component/s: MLlib
    • Labels:
      None

      Description

      The current implementations of machine learning algorithms rely on the driver for some computation and data broadcasting. This will create a bottleneck at the driver for both computation and communication, especially in multi-model training. An efficient implementation of AllReduce (or AllAggregate) can help free the driver:

      allReduce(RDD[T], (T, T) => T): RDD[T]

      This JIRA is created for discussing how to implement AllReduce efficiently and possible alternatives.

        Attachments

        Issue Links

          Activity

          $i18n.getText('security.level.explanation', $currentSelection) Viewable by All Users
          Cancel

            People

            • Assignee:
              mengxr Xiangrui Meng Assign to me
              Reporter:
              mengxr Xiangrui Meng

              Dates

              • Created:
                Updated:
                Resolved:

                Issue deployment