| commit | 53a160949cd8c40e19a852b51b3d214b64082772 | [log] [tgz] |
|---|---|---|
| author | Arnab Phani <phaniarnab@gmail.com> | Wed Apr 26 23:17:01 2023 +0200 |
| committer | Arnab Phani <phaniarnab@gmail.com> | Wed Apr 26 23:17:01 2023 +0200 |
| tree | 7584dea22f9ee3e2e836301d1169d58b06e9aa56 | |
| parent | 5a33181ee0f2f067a5c670e2d3faef565d0a86bc [diff] |
[MINOR] Fix bufferpool eviction for future objects
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
