[jira] [Updated] (SYSTEMML-1039) Add support for aggregate unary operations on GPU

["Nakul Jindal (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SYSTEMML-1039?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Nakul Jindal updated SYSTEMML-1039:
-----------------------------------
    Fix Version/s: SystemML 1.0

> Add support for aggregate unary operations on GPU
> -------------------------------------------------
>
>                 Key: SYSTEMML-1039
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-1039
>             Project: SystemML
>          Issue Type: Sub-task
>          Components: Compiler, Runtime
>         Environment: 1. Update UnaryOp to enable GPU for these instructions.
> 2. Add AggregateUnaryGPUInstruction and invoke kernels corresponding to https://github.com/apache/incubator-systemml/blob/master/src/main/java/org/apache/sysml/runtime/matrix/data/MatrixBlock.java#L4451
> Note nrow, ncol and length should always be a CP instruction. Also, we can break this into subtasks for sparse if necessary.
> The opcodes related to this tasks are: uak+, uark+, uack+, uasqk+, uarsqk+, uacsqk+, uamean, uarmean, uacmean, uavar, uarvar, uacvar, uamax, uarmax, uarimax, uacmax, uamin, uarmin, uarimin, uacmin, ua+, uar+, uac+, ua*, uatrace, uaktrace and the operations of these are (with/without kahan) sum, trace, rowsum, colsum, sum of squares, row sum of squares, col sum of squares, cumsum, cumprod, cummin, cummax, min, max, min_index, max_index, mean, variance and product.
> [~nakul02] This is a mega-task. Hopefully we can generalize our kernel implementation to make this easier.
>            Reporter: Niketan Pansare
>            Assignee: Nakul Jindal
>             Fix For: SystemML 1.0
>
>




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