commit | 5e497509ab9f2cd3218b74bf9576bee5241d95c3 | [log] [tgz] |
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author | Matthias Boehm <mboehm7@gmail.com> | Thu Feb 11 21:25:39 2021 +0100 |
committer | Matthias Boehm <mboehm7@gmail.com> | Thu Feb 11 21:25:39 2021 +0100 |
tree | 42ef17b9ded9ba28fce8438013a7ad61f64d70bb | |
parent | d9f9723198e01f3470c1f98492f647dada312a1e [diff] |
[SYSTEMDS-2860] Fix native BLAS tsmm integration (dsyrk outer products) This patch fixes an issue of the BLAS integration of dsyrk (tsmm in SystemDS), which for a row vector input and left tsmm, apparently returns the input vector. Since this operation is a memory-bandwidth bound we avoid this edge case by using the respective Java kernels. Furthermore, the tsmm runtimes where not yet included in the native BLAS runtime statistics which is now also cleaned up.
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