commit | 1ca51972a20993e49cf2f3001505d9e3af7be8f3 | [log] [tgz] |
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author | Olga <ovcharenko.folga@gmail.com> | Sat Oct 10 15:09:33 2020 +0200 |
committer | baunsgaard <baunsgaard@tugraz.at> | Sat Oct 10 15:31:57 2020 +0200 |
tree | 81dac73f4aa721e96ca498d1168170d5edbaa85c | |
parent | ab08fc5f45b74f4dbd57136ec2c735b0d37cd7a6 [diff] |
[SYSTEMDS-2681] Federated Bivariate Statistics SYSTEMDS 2543-2544 Federated Aggregations: - Federated Min + Max col and row aggregation - Federated mean and sum aggregations Closes #1040
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