commit | 472d778b4c0713b6df6b3a10bcfd7475ef167cc8 | [log] [tgz] |
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author | baunsgaard <baunsgaard@tugraz.at> | Tue Oct 13 14:14:06 2020 +0200 |
committer | baunsgaard <baunsgaard@tugraz.at> | Mon Oct 19 11:34:27 2020 +0200 |
tree | 5c5fcaab53a424453bc4d3403ec5e661d4bb5870 | |
parent | 461ee22559106130ead12f8b5fc1fb2aa0c4f6f8 [diff] |
[SYSTEMDS-2686] Compressed overlapping column groups This commit change the compressed right multiplication to perform in compressed space, resulting in significantly faster execution. The technique employed results in overlapping column groups, that contain partial results of the matrix multiplication. The downside is that some operations that previously was possible on compressed space no longer works, for the overlapping column groups. To still support all the operations, then decompression is used for cases where it is impossible to execute on the compressed matrices. Another addition is that statistics now contain compression and decompression times if compression is enabled. Furthermore the tests have been extended to include tests for the overlapping resulting in + 10000 tests in compression now.
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