commit | b6a18804c6d17a67355e1657f54d3b7d362c73a1 | [log] [tgz] |
---|---|---|
author | Matthias Boehm <mboehm7@gmail.com> | Thu Dec 31 20:51:33 2020 +0100 |
committer | Matthias Boehm <mboehm7@gmail.com> | Thu Dec 31 20:51:33 2020 +0100 |
tree | 284e3b75a2383b5def98ad3d5b1e29b9d428f291 | |
parent | 43ed96efe29a6b3e46ad64179b1e4e07995cbcdf [diff] |
[MINOR] Fix arima test (flag as thread-unsafe test to avoid inference)
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