commit | 0968c3b1fb2e88d279e71a3cde6154a163d2baf0 | [log] [tgz] |
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author | sebwrede <swrede@know-center.at> | Thu Dec 17 11:37:17 2020 +0100 |
committer | Matthias Boehm <mboehm7@gmail.com> | Thu Dec 17 11:47:20 2020 +0100 |
tree | 163d219163ee2b337398d7f10d8c1a9a2c428ffd | |
parent | 0d5e94ace91b9883f9e64d3156ae405a6b3c4bea [diff] |
[SYSTEMDS-2759] Add federated lmCG test for rewrite debugging Closes #1126.
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