+1 Ran the performance suite on an IBM internal cluster. Most tests seem to perform reasonably close to the previous release.
-Nakul On Fri, Apr 28, 2017 at 5:51 PM, Matthias Boehm <mboe...@googlemail.com> wrote: > this regression is certainly something to look into but this release > contains a large number of fixes including many that addressed severe OOM > issues, so it might in fact be just an issue of more conservative but now > correct execution plans given the current capabilities of our compiler. > > Regards, > Matthias > > On Fri, Apr 28, 2017 at 5:39 PM, <dusenberr...@gmail.com> wrote: > > > +1 Grabbed the tar binary and the tar source and tested various local > > scripts in Scala & Python 2 + 3, and those ran fine. However, I did run > > the MNIST LeNet demo on both our 0.13 release and this 0.14 candidate, > and > > I noticed a regression in 0.14. For the same script run back to back, > the > > 0.14 candidate took longer, and looking into the stats, on 0.13 there > were > > 864 Spark instructions executed, while on this 0.14 there were 2513 Spark > > instructions executed. This also brought the `sp_mapmm` and `sp_sel+` > > instructions into the top 10 heavy hitters. This could be related to the > > issue that I am seeing in SYSTEMML-1561. > > > > Regardless, I'm still fine with releasing this, since the deep learning > > support is still experimental for 0.14. For our upcoming 1.0 release, > all > > engine bugs and issues related to deep learning need to be fixed. Most > of > > these bugs are generally applicable to all algorithms, so it is in the > > benefit of the project to fix them. > > > > -- > > > > Mike Dusenberry > > GitHub: github.com/dusenberrymw > > LinkedIn: linkedin.com/in/mikedusenberry > > > > Sent from my iPhone. > > > > > > > On Apr 28, 2017, at 10:37 AM, Arvind Surve <ac...@yahoo.com.INVALID> > > wrote: > > > > > > +1 > > > Completed following verifications - License and Notice validations > - > > Binary runtime validations - Source code compilation and runtime > > validations - Python scripts validations using Python 2 Arvind Surve | > > Spark Technology Center | http://www.spark.tc/ > > > > > > From: Glenn Weidner <gweid...@us.ibm.com> > > > To: dev@systemml.incubator.apache.org > > > Sent: Monday, April 24, 2017 9:30 PM > > > Subject: Re: [VOTE] Apache SystemML 0.14.0-incubating (RC4) > > > > > > +1 > > > > > > Successfully ran Linear Regression, Logistic Regression, Naive Bayes, > > SVM in > > > Python notebooks with Spark 2.0.2 (in cloud environment) and Spark 2.1 > > (on local test cluster) after pip install of RC4 python artifact > > > systemml-0.14.0-incubating-python.tgz. Also ran Linear Regression > > Conjugate Gradient in Scala notebooks. > > > > > > Regards, > > > Glenn > > > > > > Matthias Boehm ---04/24/2017 02:02:12 AM---+1 I ran large-scale > > experiments on Spark 2.1 for L2SVM, GLM, MLogreg, > > > > > > From: Matthias Boehm <mboe...@googlemail.com> > > > To: dev@systemml.incubator.apache.org > > > Date: 04/24/2017 02:02 AM > > > Subject: Re: [VOTE] Apache SystemML 0.14.0-incubating (RC4) > > > > > > > > > > > > +1 > > > > > > I ran large-scale experiments on Spark 2.1 for L2SVM, GLM, MLogreg, > > > LinregCG, LinregDS, and PCA over scaled versions of MNIST and ImageNet > > (up > > > to 1TB, with uncompressed and compressed linear algebra) without any > > > issues. > > > > > > Compared to previous experiments with SystemML 0.11 and Spark 1.6, I've > > > seen substantial performance improvements of >2x for iterative > algorithms > > > with RDD operations in the inner loop over out-of-core datasets. > > > > > > Regards, > > > Matthias > > > > > > On Wed, Apr 19, 2017 at 4:17 PM, Arvind Surve <ac...@yahoo.com.invalid > > > > > wrote: > > > > > >> Please vote on releasing the following candidate as Apache SystemML > > >> version 0.14.0-incubating ! > > >> The vote is open for at least 72 hours and passes if a majority of at > > >> least 3 +1 PMC votes are cast. > > >> [ ] +1 Release this package as Apache SystemML 0.14.0-incubating[ ] -1 > > Do > > >> not release this package because ... > > >> To learn more about Apache SystemML, please see > http://systemml.apache. > > >> org/ > > >> The tag to be voted on is v0.14.0-incubating-rc4 ( > > >> 8bdcf106ca9bd04c0f68924ad5827eb7d7d54952) > > >> https://github.com/apache/incubator-systemml/commit/ > > >> 8bdcf106ca9bd04c0f68924ad5827eb7d7d54952 > > >> > > >> The release artifacts can be found at :https://dist.apache.org/ > > >> repos/dist/dev/incubator/systemml/0.14.0-incubating-rc4/ > > >> The maven release artifacts, including signatures, digests, etc. can > > >> be found at:https://repository.apache.org/content/repositories/ > > >> orgapachesystemml-1021/org/apache/systemml/systemml/0.14. > 0-incubating/ > > >> ======================================= Apache Incubator release > policy > > >> =======================================Please find below the guide to > > >> release management during incubation:http://incubator. > > apache.org/guides/ > > >> releasemanagement.html > > >> ========================================= How can I help test this > > >> release? =========================================If you are a > SystemML > > >> user, you can help us test this release by taking an existing > Algorithm > > or > > >> workload and running on this release candidate, thenreporting any > > >> regressions. > > >> ================================================== What justifies a > -1 > > >> vote for this release? ============================== > > ====================-1 > > >> votes should only occur for significant stop-ship bugs or legal > > >> related issues (e.g. wrong license, missing header files, etc). Minor > > bugs > > >> or regressions should not block this release. > > >> -Arvind > > >> Arvind Surve | Spark Technology Center | http://www.spark.tc/ > > > > > > > > > > > > > > > > > >
