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https://issues.apache.org/jira/browse/SYSTEMML-2085?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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LI Guobao updated SYSTEMML-2085:
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Description:
Parameter server allows to persist the model parameters in a distributed
manner. It is specially applied in the context of large-scale machine learning
to train the model. The parameters computation will be done with data
parallelism across the workers. The data-parallel parameter server architecture
is illustrated in Figure 2. With the help
of a lightweight parameter server interface [1], we are inspired to provide the
push and pull methods as internal primitives, i.e., not exposed to the script
level, allowing to exchange the intermediates among workers.
> Single-node parameter server primitives
> ---------------------------------------
>
> Key: SYSTEMML-2085
> URL: https://issues.apache.org/jira/browse/SYSTEMML-2085
> Project: SystemML
> Issue Type: Sub-task
> Reporter: Matthias Boehm
> Assignee: LI Guobao
> Priority: Major
>
> Parameter server allows to persist the model parameters in a distributed
> manner. It is specially applied in the context of large-scale machine
> learning to train the model. The parameters computation will be done with
> data parallelism across the workers. The data-parallel parameter server
> architecture is illustrated in Figure 2. With the help
> of a lightweight parameter server interface [1], we are inspired to provide
> the push and pull methods as internal primitives, i.e., not exposed to the
> script level, allowing to exchange the intermediates among workers.
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