commit | 83400bb0f239a60e9c44444fe5977ee304f611f0 | [log] [tgz] |
---|---|---|
author | Shafaq Siddiqi <shafaq.siddiqi@tugraz.at> | Sat Dec 19 22:32:23 2020 +0100 |
committer | Matthias Boehm <mboehm7@gmail.com> | Sat Dec 19 22:32:52 2020 +0100 |
tree | af2e701b2691222868b6af6c94622b4485eb1ac2 | |
parent | c54213df08b259fc3b8c96d4c3ffe6b0ea6b1eb1 [diff] |
[SYSTEMDS-2764] Frame constructor and data-gen operations DIA project WS2020/21. Closes #1132.
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.
Quick Start Install, Quick Start and Hello World
Documentation: SystemDS Documentation
Python Documentation Python SystemDS Documentation
Issue Tracker Jira Dashboard
Status and Build: SystemDS is renamed from SystemML which is an Apache Top Level Project. To build from source visit SystemDS Install from source