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https://issues.apache.org/jira/browse/SYSTEMML-2092?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Matthias Boehm updated SYSTEMML-2092:
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Description:
So far, parfor loops only support left and right indexing operations over
result variables. The related result merge then simply merges the partial
worker results with or without compare matrix. However, there are many use
cases that would benefit from additional result aggregation functions.
This task aims to introduce a new {{R += A}} accumulator operation to address
the above challenge. The semantics are equivalent to {{R = R + A}}, but the
parfor dependency analysis will recognize this as a special aggregation
function instead of throwing an error due to output dependencies.
was:
So far, parfor loops only support left and right indexing operations over
result variables. The related result merge then simply merges the partial
worker results with or without compare matrix. However, there are many use
cases that would benefit from additional result aggregation functions.
This task aims to introduce a new \{{R += A}} accumulator operation to address
the above challenge. The semantics are equivalent to R = R + A, but the parfor
dependency analysis will recognize this as a special aggregation function
instead of throwing an error due to output dependencies.
> Parfor result aggregation
> -------------------------
>
> Key: SYSTEMML-2092
> URL: https://issues.apache.org/jira/browse/SYSTEMML-2092
> Project: SystemML
> Issue Type: Task
> Reporter: Matthias Boehm
> Priority: Major
>
> So far, parfor loops only support left and right indexing operations over
> result variables. The related result merge then simply merges the partial
> worker results with or without compare matrix. However, there are many use
> cases that would benefit from additional result aggregation functions.
>
> This task aims to introduce a new {{R += A}} accumulator operation to address
> the above challenge. The semantics are equivalent to {{R = R + A}}, but the
> parfor dependency analysis will recognize this as a special aggregation
> function instead of throwing an error due to output dependencies.
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