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https://issues.apache.org/jira/browse/SYSTEMML-1451?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15998541#comment-15998541
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Krishna Kalyan edited comment on SYSTEMML-1451 at 5/5/17 4:39 PM:
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Hello [~nakul02],
This is a performance test for `genBinomialData` with less than `80` MB data.
Yes, the default config is little bit too much for my PC. I tried using this to
limit jvm usage `export JAVA_OPTS="-Xmx2G -Xms2g -Xmn1g"`. However the problem
still persists. Could you please guide on how to set limits via the environment
variables?/ configuration file?.
Regards,
Krishna
was (Author: krishnakalyan3):
Hello [~nakul02],
This is a performance test for `genBinomialData` with less than `80` MB data.
Yes, the default config is set to high for my PC. I tried using this to limit
jvm usage `export JAVA_OPTS="-Xmx2G -Xms2g -Xmn1g"`. However my script still
fails. Could you please guide on how to set limits via the environment
variables?/ configuration file?.
Regards,
Krishna
> Automate performance testing and reporting
> ------------------------------------------
>
> Key: SYSTEMML-1451
> URL: https://issues.apache.org/jira/browse/SYSTEMML-1451
> Project: SystemML
> Issue Type: Improvement
> Components: Infrastructure, Test
> Reporter: Nakul Jindal
> Labels: gsoc2017, mentor, performance, reporting, testing
>
> As part of a release (and in general), performance tests are run for SystemML.
> Currently, running and reporting on these performance tests are a manual
> process. There are helper scripts, but largely the process is manual.
> The aim of this GSoC 2017 project is to automate performance testing and its
> reporting.
> These are the tasks that this entails
> 1. Automate running of the performance tests, including generation of test
> data
> 2. Detect errors and report if any
> 3. Record performance benchmarking information
> 4. Automatically compare this performance to previous version to check for
> performance regressions
> 5. Automatically compare to Spark MLLib, R?, Julia?
> 6. Prepare report with all the information about failed jobs, performance
> information, perf info against other comparable projects/algorithms
> (plotted/in plain text in CSV, PDF or other common format)
> 7. Create scripts to automatically run this process on a cloud provider that
> spins up machines, runs the test, saves the reports and spins down the
> machines.
> 8. Create a web application to do this interactively without dropping down
> into a shell.
> As part of this project, the student will need to know scripting (in Bash,
> Python, etc). It may also involve changing error reporting and performance
> reporting code in SystemML.
> Rating - Medium (for the amount of work)
> Mentor - [~nakul02] (Other co-mentors will join in)
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