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From "Mike Dusenberry (JIRA)" <>
Subject [jira] [Commented] (SYSTEMML-1774) Improve Parfor parallelism for deep learning
Date Tue, 18 Jul 2017 22:08:00 GMT


Mike Dusenberry commented on SYSTEMML-1774:

[~mboehm7]  Okay, thanks.  I would have thought that Spark execution mode would force the
parfor op to be run as a distributed spark operation, and thus the bodies would be forced
to CP operations running on each worker.  Sounds like it is the opposite: the parfor runs
as a local CP parfor, and the bodies consist of Spark ops if possible.

Do you have any thoughts as to why the SPARK execution mode is 3x faster than the HYBRID_SPARK
execution mode?

> Improve Parfor parallelism for deep learning
> --------------------------------------------
>                 Key: SYSTEMML-1774
>                 URL:
>             Project: SystemML
>          Issue Type: Improvement
>          Components: Algorithms, Compiler, ParFor
>    Affects Versions: SystemML 1.0
>            Reporter: Fei Hu
>              Labels: deeplearning
>         Attachments: Explain_For_HYBRID_SPARK_Mode_With_ErrorInfo.txt, Explain_For_Spark_Mode.txt,
MNIST_Distrib_Sgd.scala, mnist_lenet_distrib_sgd.dml
> When running the  [distributed MNIST LeNet example |],
each mini-batch could ideally run in parallel without interaction. We try to force {{parfor
(j in 1:parallel_batches)}} at line 137 of {{nn/examples/mnist_lenet_distrib_sgd.dml}} to
be {{parfor (j in 1:parallel_batches, mode=REMOTE_SPARK, opt=CONSTRAINED)}} use {{REMOTE_SPARK}}
mode, but got some errors about {{org.apache.sysml.runtime.DMLRuntimeException: Not supported:
Instructions of type other than CP instructions}} using the mode {{SPARK}}, and the error
{{java.lang.NullPointerException}} using the mode {{HYBRID_SPARK}}. More log information can
be found at the following comments. 

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