[ https://issues.apache.org/jira/browse/SYSTEMML2046?page=com.atlassian.jira.plugin.system.issuetabpanels:alltabpanel
]
Matthias Boehm updated SYSTEMML2046:

Description:
This task aims to add support for large dense blocks to all amenable matrix block operations.
In order to allow for incremental progress, we handle the following categories of operations
separately:
* Matrix multiplications
* Unary and grouped aggregates
* Unary and binary elementwise operations
* Reorg operations (e.g., transpose, sort, removeEmpty)
* Left and right indexing operations, incl updateinplace
* Deep learning operations (e.g., conv2d, maxpool)
* Codegen cell, row, outer operations
* Compressed linear algebra
* Remaining operations (e.g., parfor result merge)
After all categories of operations are reimplemented accordingly, the testsuite should be
run with forced large dense blocks and constant block size of 10 in order to emulate the large
dense block which otherwise would require input data >16GB.
> Operations over large dense blocks
> 
>
> Key: SYSTEMML2046
> URL: https://issues.apache.org/jira/browse/SYSTEMML2046
> Project: SystemML
> Issue Type: Subtask
> Reporter: Matthias Boehm
> Fix For: SystemML 1.1
>
>
> This task aims to add support for large dense blocks to all amenable matrix block operations.
In order to allow for incremental progress, we handle the following categories of operations
separately:
> * Matrix multiplications
> * Unary and grouped aggregates
> * Unary and binary elementwise operations
> * Reorg operations (e.g., transpose, sort, removeEmpty)
> * Left and right indexing operations, incl updateinplace
> * Deep learning operations (e.g., conv2d, maxpool)
> * Codegen cell, row, outer operations
> * Compressed linear algebra
> * Remaining operations (e.g., parfor result merge)
> After all categories of operations are reimplemented accordingly, the testsuite should
be run with forced large dense blocks and constant block size of 10 in order to emulate the
large dense block which otherwise would require input data >16GB.

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