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https://issues.apache.org/jira/browse/SYSTEMML-2197?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Matthias Boehm closed SYSTEMML-2197.
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Resolution: Fixed
Fix Version/s: SystemML 1.2
> Multi-threaded broadcast creation
> ---------------------------------
>
> Key: SYSTEMML-2197
> URL: https://issues.apache.org/jira/browse/SYSTEMML-2197
> Project: SystemML
> Issue Type: Task
> Reporter: Matthias Boehm
> Assignee: LI Guobao
> Priority: Major
> Fix For: SystemML 1.2
>
>
> All spark instructions that broadcast one of the input operands, rely on a
> shared primitive {{sec.getBroadcastForVariable(var)}} for creating
> partitioned broadcasts, which are wrapper objects around potentially many
> broadcast variables to overcome Spark 2GB limitation for compressed
> broadcasts. Each individual broadcast blocks the matrix into squared blocks
> for direct access without unnecessary copy per task. So far this broadcast
> creation is single-threaded.
> This task aims to parallelize the blocking of the given in-memory matrix into
> squared blocks
> (https://github.com/apache/systemml/blob/master/src/main/java/org/apache/sysml/runtime/instructions/spark/data/PartitionedBlock.java#L82)
> as well as the subsequent partition creation and actual broadcasting
> (https://github.com/apache/systemml/blob/master/src/main/java/org/apache/sysml/runtime/controlprogram/context/SparkExecutionContext.java#L548).
>
> For consistency and in order to avoid excessive over-provisioning, this
> multi-threading should use the common internal thread pool or parallel java
> streams, which similarly calls the shared {{ForkJoinPool.commonPool}}. An
> example is the multi-threaded parallelization of RDDs which similarly blocks
> a given matrix into its squared blocks (see
> https://github.com/apache/systemml/blob/master/src/main/java/org/apache/sysml/runtime/controlprogram/context/SparkExecutionContext.java#L679).
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