| commit | 6f44461692b5e3eea2a1554425ce6228ae4ddea2 | [log] [tgz] |
|---|---|---|
| author | Matthias Boehm <mboehm7@gmail.com> | Sat May 23 00:02:00 2020 +0200 |
| committer | Matthias Boehm <mboehm7@gmail.com> | Sat May 23 00:03:58 2020 +0200 |
| tree | 5975a94f5748244ad55ea6d8944a21aa09087b62 | |
| parent | f29ae426be1722fba9468609976709068e6e5d7d [diff] |
[MINOR] Performance lineage tracing of literal operands
This patch makes a minor performance improvement reuse thread-local
string builders (as done for instructions) for the construction for
lineage literals as well.
On the following reduced example script, this patch improved the total
execution time from 56s to 50.3s due to partially removed garbage
collection overhead:
X = rand(rows=10, cols=10, seed=1);
for(i in 1:1e6) {
tmp1 = ((X + 1) * 2) / 3
tmp2 = (tmp1 - 1) * tmp1
X = tmp2;
if( i%%1e5==0 )
print("Iteration "+i);
}
print(sum(X));
Notice that this script creates over one million lineage items for
literals to cover the 1e6 distinct values of the loop variable i.
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
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.
