| commit | 4d0aa9fe93c8d33a1d91f9ec3d243dfc00fccc42 | [log] [tgz] |
|---|---|---|
| author | Sebastian <baunsgaard@tugraz.at> | Mon Mar 23 14:48:54 2020 +0100 |
| committer | Sebastian <baunsgaard@tugraz.at> | Mon Mar 23 14:48:54 2020 +0100 |
| tree | 23d105088efb6d5d0a9632624af8c99bc2108aa1 | |
| parent | 8328b2cd7cdf0243d257ea28eff082295aebffbe [diff] |
[SYSTEMDS-305] Docker containers for speedup of Github actions - Added docker folder for docker constructions. Now we have a docker container able to execute any given DML script in a nice easy to use one liner. More information in docker/README.md - Added .github/action for custom github actions. Made custom github action for our testing framework to reduce startup time from 16-17 min to 5 min, before executing tests using R. Minor change: - Only build documentation on master branch Closes #122
Overview: SystemDS is a versatile system for the end-to-end data science lifecycle from data integration, cleaning, and feature engineering, over efficient, local and distributed ML model training, to deployment and serving. To this end, we aim to provide a stack of declarative languages with R-like syntax for (1) the different tasks of the data-science lifecycle, and (2) users with different expertise. These high-level scripts are compiled into hybrid execution plans of local, in-memory CPU and GPU operations, as well as distributed operations on Apache Spark. In contrast to existing systems - that either provide homogeneous tensors or 2D Datasets - and in order to serve the entire data science lifecycle, the underlying data model are DataTensors, i.e., tensors (multi-dimensional arrays) whose first dimension may have a heterogeneous and nested schema.
Documentation: SystemDS Documentation
Status and Build: SystemDS is still in pre-alpha status. The original code base was forked from Apache SystemML 1.2 in September 2018. We will continue to support linear algebra programs over matrices, while replacing the underlying data model and compiler, as well as substantially extending the supported functionalities. Until the first release, you can build your own snapshot via Apache Maven: mvn -DskipTests clean package.
