| commit | 2c5f70353b3863db68442fd57b5db7ed6ca4196d | [log] [tgz] |
|---|---|---|
| author | Matthias Boehm <mboehm7@gmail.com> | Sat Sep 12 15:47:58 2020 +0200 |
| committer | Matthias Boehm <mboehm7@gmail.com> | Sat Sep 12 15:47:58 2020 +0200 |
| tree | aea646c46b43cf58089cddc7adc2880e4489152d | |
| parent | 9e512199ea81bca6fc9df73b4c3792a2c101d2ef [diff] |
[SYSTEMDS-2641] Improved slice finding dml algorithm (perf, correctness) This patch fixes the correctness of the slice finding where the generation of paired candidates mistakenly used upper.tri instead of upper.tri-values which created invalid slices and violated the expected monotonicity properties. Furthermore this patch also includes two major performance improvements, specifically (1) the pruning before candidate generation (which does not affect overall pruning effectiveness due to the handling of missing parents), and (2) an ID transformation to avoid exceeding integer-max for many columns and to avoid huge sparse intermediates. These changes improved the runtime on a replicated (more rows and columns) salary dataset from 799s to 52s (only 1), and 2.6s (1 and 2) respectively.
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 still in pre-alpha status. The original code base was forked from Apache SystemML 1.2 in September 2018. We will continue to support linear algebra programs over matrices, while replacing the underlying data model and compiler, as well as substantially extending the supported functionalities. Until the first release, you can build your own snapshot via Apache Maven: mvn clean package -P distribution.
