commit | ceb50a2d2175390267796e0cfd8620ca251c1e3d | [log] [tgz] |
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author | ReneEnjilian <enjilianrene@gmail.com> | Sat Jan 20 01:00:12 2024 +0100 |
committer | Matthias Boehm <mboehm7@gmail.com> | Sat Jan 20 17:35:35 2024 +0100 |
tree | c50355559e90e6f176193190d1d37c60792821e9 | |
parent | d69723797a3b1ee9d5491691f53d216e1a24802b [diff] |
[SYSTEMDS-3665] New rewrite for mmult-add expressions A%*%B + A%*%C -> A%*%(B+C) iff A, B, and C dense and the target expression reduces the number of floating points operations. Closes #1986.
Overview: SystemDS is an open source ML 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