commit | 178d0f04ffc5fab15e487d918b6cbe95abdcc50e | [log] [tgz] |
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author | baunsgaard <baunsgaard@tugraz.at> | Tue Oct 20 21:55:12 2020 +0200 |
committer | baunsgaard <baunsgaard@tugraz.at> | Tue Nov 24 12:49:31 2020 +0100 |
tree | a914df4700f77ba9f2ef8c4f2854014a0cf0ab44 | |
parent | a05884ad2f042644bde0be23129ed1c5ca8246cb [diff] |
[SYSTEMDS-2696] Overlapping relational operations This commit adds relational support for relational operations, (< > <= etc) in the compressed space, for overlapping matrices. If the relational expression returns a constant matrix, the operations are super fast, while if the output is mixed it performs okay compared to our uncompressed. Further optimizations are available, but since this operation is not critical it is not explored yet.
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