commit | 998d82e27b8add5a0ca55ac687f0bfd9abe54c8b | [log] [tgz] |
---|---|---|
author | Matthias Boehm <mboehm7@gmail.com> | Sat Oct 31 20:25:59 2020 +0100 |
committer | Matthias Boehm <mboehm7@gmail.com> | Sat Oct 31 21:42:22 2020 +0100 |
tree | 2c80aa3ab375de3c9542bee5d0a56a35c7aed186 | |
parent | 3d97048e457a00af9288a9940f962392df3abcbc [diff] |
[SYSTEMDS-2549] Extended federated binary element-wise operations This patch generalizes the existing federated binary element-wise operations to avoid unsupported scenarios. Specifically, if the right-hand-side matrix (instead of left-hand-side) matrix is federated and the operation is commutative (e.g., mult/add) we canonicalize the inputs accordingly.
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