commit | 769f0e3db1646acdb7212bbe0c2275d69013a2c2 | [log] [tgz] |
---|---|---|
author | Mark Dokter <mark@dokter.cc> | Mon Apr 12 23:06:32 2021 +0200 |
committer | Mark Dokter <mark@dokter.cc> | Mon Apr 12 23:06:32 2021 +0200 |
tree | fa3884fb3803715cc636dd9f2ca7aab90f18c098 | |
parent | 5c63f3056a741360de77478e9c5d52246bb26786 [diff] |
[SYSTEMDS-2888] Fix incomplete cbind support in codegen row templates (CUDA) This patch is the CUDA version of the original bugfix (commit 1ec292a932c6e732bbac835a81cdb59371002114)
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