commit | 4a62c5214c0a08edf492ce49dc5841f4c7600a15 | [log] [tgz] |
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author | Matthias Boehm <mboehm7@gmail.com> | Fri Aug 05 15:03:51 2022 +0200 |
committer | Matthias Boehm <mboehm7@gmail.com> | Fri Aug 05 15:31:38 2022 +0200 |
tree | dc35b744dcd4e782b42830f3e501afc17321feee | |
parent | 47ea25f624c178e155371637d6b2528064a9a88f [diff] |
[SYSTEMDS-3417] Fix integer overflow in fast-buffered-input-stream This patch fixes an integer overflow---encountered when deserializing large, multi-array matrix blocks---where the individual chunks are close to INT_MAX. In such cases, the integer loop variable i+=_bufflen/8 did overflow on the increment by += (bufflen (default 8K) div 8), running into index-out-of-bounds with negative indexes.
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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Documentation: SystemDS Documentation
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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