commit | 36507ce4e1aed403742a144b8bfecd1bae5ba749 | [log] [tgz] |
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author | Arnab Phani <phaniarnab@gmail.com> | Wed Jun 07 20:02:39 2023 +0200 |
committer | Arnab Phani <phaniarnab@gmail.com> | Wed Jun 07 20:02:39 2023 +0200 |
tree | a899ce418328efeecc284a5b6bc4c2f466829ddc | |
parent | a8fdd648998ed5e645c0f02d28bfb457a1bd297b [diff] |
[SYSTEMDS-3566] Heuristic-based operator placement policy for GPU This patch adds a few rules to move GPU operators to CP. Examples include sparse operation and GPU operator sandwiched between CP operators. This policy is implemented as a Lop rewrite. Closes #1837
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