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 --------------------
