Looks good. We should also include the VLDB paper award. --
Mike Dusenberry GitHub: github.com/dusenberrymw LinkedIn: linkedin.com/in/mikedusenberry Sent from my iPhone. > On Nov 1, 2016, at 4:43 PM, Deron Eriksson <deroneriks...@gmail.com> wrote: > > Hello, > > Here is a draft of the November monthly report due tomorrow that Felix and > I put together. Feedback is welcome. > > Deron > > -------------------- > > SystemML > > SystemML provides declarative large-scale machine learning (ML) that aims at > flexible specification of ML algorithms and automatic generation of hybrid > runtime plans ranging from single node, in-memory computations, to > distributed > computations running on Apache Hadoop MapReduce and Apache Spark. > > SystemML has been incubating since 2015-11-02. > > Three most important issues to address in the move towards graduation: > > - Grow SystemML community: increase mailing list activity, > increase adoption of SystemML for scalable machine learning, encourage > data scientists to adopt DML and PyDML algorithm scripts, respond to > user feedback to ensure SystemML meets the requirements of real-world > situations, write papers, and present talks about SystemML. > - Continue to produce releases. > - Increase the diversity of our project's contributors and committers. > > Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be aware > of? > > NONE. > > How has the community developed since the last report? > Our mailing list from August through October had 375 messages on a wide > range > of topics. We have gained 4 new contributors to the main project since > August > 1st. Our website has been redesigned with the help of several design > engineers > and we have commits from 3 new contributors to the website project. On > GitHub, > the project has been starred 417 times and forked 156 times. > > Niketan Pansare gave a talk with the title "Apache SystemML - Declarative > Machine Learning at Scale" on October 7th in the CS graduate seminar at UC > Merced. Matthias Boehm gave a talk on "Compressed Linear Algebra for Large- > Scale Machine Learning" at TU Dresden on August 30th. We presented the > papers > "Compressed Linear Algebra for Large-Scale Machine Learning" (research > paper + > poster) and "SystemML: Declarative Machine Learning on Spark" (industry > paper) > at VLDB'16, gave two 90 minute tutorials at the BOSS'16 workshop, > co-located > with VLDB'16, and our paper "SPOOF: Sum-Product Optimization and Operator > Fusion for Large- Scale Machine Learning" has been accepted at CIDR'17. > > How has the project developed since the last report? > The main project has had 213 commits since August 1. The website project > has > had 51 commits since August 1. Since August 1, 241 issues have been > reported > on our JIRA site and 137 issues have been resolved or closed. 79 pull > requests > have been created since August 1, and 72 pull requests have been closed. > > Date of last release: > > 2016-06-15 (version 0.10.0-incubating) > > When were the last committers or PMC members elected? > > 2016-05-07 Glenn Weidner > 2016-05-07 Faraz Makari Manshadi > > --------------------
