| commit | 5015f63a7980f36e832bdffcbebba575cf8ddd62 | [log] [tgz] |
|---|---|---|
| author | Matthias Boehm <mboehm7@gmail.com> | Fri Jun 07 09:44:45 2024 +0200 |
| committer | Matthias Boehm <mboehm7@gmail.com> | Fri Jun 07 09:44:45 2024 +0200 |
| tree | efac075d8b49f05ec107aa9d4e3886a688181965 | |
| parent | da7889eb1f7e1a831903fc513aa3906f995e2dfd [diff] |
[SYSTEMDS-3709] Additional tests for UDF backwards compatibility This patch adds tests for the old SystemML UDF MultiInputCbind, ensuring the related DML script is properly compiled to an nary cbind and if the inputs are vectors and are reshaped to vectors, we also eliminate the unnecessary reshape.
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.
| Resource | Links |
|---|---|
| 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
