[MINOR] Additional single-/multi-threaded tests for matmult kernels

This patch adds dedicated components tests for all matmult kernels
(different kernels for dense-dense, dense-sparse, sparse-dense,
sparse-sparse) and checks both single- and multi-threaded
implementations because SYSTEMDS-3769 recently shown that some of these
kernels invalid parallelization strategies.

Interestingly, these tests revealed two additional bugs for
(1) dense-dense outer products, and (2) sparse-dense inner products.

Furthermore, we also fix the missing license introduced with
a recently merged PR.
3 files changed
tree: 9a158a60cb77bbec661636a808c24458834b39ca
  1. .github/
  2. .mvn/
  3. bin/
  4. conf/
  5. dev/
  6. docker/
  7. docs/
  8. scripts/
  9. src/
  10. .asf.yaml
  11. .gitattributes
  12. .gitignore
  13. .gitmodules
  14. CITATION
  15. codecov.yml
  16. CONTRIBUTING.md
  17. doap.rdf
  18. LICENSE
  19. NOTICE
  20. pom.xml
  21. README.md
README.md

Apache SystemDS

Overview: SystemDS is an open source ML 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

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