| commit | 3ce32709366203eccb8da9063cedafa567f8d3bf | [log] [tgz] |
|---|---|---|
| author | Matthias Boehm <mboehm7@gmail.com> | Thu Dec 17 23:04:18 2020 +0100 |
| committer | Matthias Boehm <mboehm7@gmail.com> | Thu Dec 17 23:04:18 2020 +0100 |
| tree | 95eff92f0118cb295ee1fce9f9351885668a7971 | |
| parent | ed8b5f5c725526f8414d2dbe9113d52260597352 [diff] |
[SYSTEMDS-2760] Performance sparse-sparse transpose operations This patch makes two minor performance improvements to multi-threaded sparse-sparse transpose operations. The tasks get column groups of the input and append outputs to the sparse output rows. For tall&skinny sparse matrices there were two shortcomings. First, we aligned the minimum column group size to 8, which is only required for dense-dense transpose operations. This improved performance on above scenario. Second, if the number of cores is larger than the number of columns, cache blocking and related position maintenance only adds unnecessary overhead. Accordingly, we now use added a special case for these scenarios. On a scenario of a 2.5M x 50 matrix with sparsity = 0.1, the total execution time of 10 transpose operations improved from 2.7s to 2.5s (with 1) and 1.9s (with 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.
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Status and Build: SystemDS is renamed from SystemML which is an Apache Top Level Project. To build from source visit SystemDS Install from source
