| commit | a4f992ed86d92cff95b160dab0c852b5434bed25 | [log] [tgz] |
|---|---|---|
| author | Matthias Boehm <mboehm7@gmail.com> | Sat Aug 08 20:51:25 2020 +0200 |
| committer | Matthias Boehm <mboehm7@gmail.com> | Sat Aug 08 20:51:55 2020 +0200 |
| tree | f887b05ef56d33239d3b62b381e1a58c293bdb78 | |
| parent | 7af2ae04f28ddcb36158719a25a7fa34b22d3266 [diff] |
[SYSTEMDS-2600] Rework federated runtime backend (framework, ops) This patch makes a major rework of the exiting federated runtime backend and operations in order to simplify the joint development of all remaining federated operations. The new design has only four command types: read, put, get, exec_inst, which allows to read federated matrices, put and get variables, and execute arbitrary instructions over these variables. With this approach, we can reuse the existing symbol table and CP/Spark instructions and only need to handle their orchestration and global compensations. Furthermore, the new design adds several primitives like broadcast, broadcastSliced, aggregations, and rbind/cbind and more convenient data structures. Finally, this patch also includes minor reworks of the execution context, and reblock rewrite to allow for specific characteristics of federated execution.
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.
