Creative Commons Attribution 3.0 Germany license (CC BY 3.0 DE)when quoting this document, please refer to the following
DOI: 10.4230/DARTS.5.2.2
URN: urn:nbn:de:0030-drops-107793
URL: https://drops.dagstuhl.de/opus/volltexte/2019/10779/
Springer, Matthias ; Masuhara, Hidehiko
DynaSOAr: A Parallel Memory Allocator for Object-Oriented Programming on GPUs with Efficient Memory Access (Artifact)
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Abstract
This artifact contains the source code of DynaSOAr, a CUDA framework for Single-Method Multiple-Objects (SMMO) applications. SMMO is a type of object-oriented programs in which parallelism is expressed by running the same method on all applications of a type. DynaSOAr is a dynamic memory allocator, combined with a data layout DSL and a parallel do-all operation. This artifact provides a tutorial explaining the API of DynaSOAr, along with nine benchmark applications from different domains. All benchmarks can be configured to use a different memory allocator to allow for a comparison with other state-of-the-art memory allocators.
BibTeX - Entry
@Article{springer_et_al:DARTS:2019:10779,
author = {Matthias Springer and Hidehiko Masuhara},
title = {{DynaSOAr: A Parallel Memory Allocator for Object-Oriented Programming on GPUs with Efficient Memory Access (Artifact)}},
pages = {2:1--2:2},
journal = {Dagstuhl Artifacts Series},
ISSN = {2509-8195},
year = {2019},
volume = {5},
number = {2},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2019/10779},
doi = {10.4230/DARTS.5.2.2},
annote = {Keywords: CUDA, Data Layout, Dynamic Memory Allocation, GPUs, Object-oriented Programming, SIMD, Single-Instruction Multiple-Objects, Structure of Arrays}
}
| Keywords: | CUDA, Data Layout, Dynamic Memory Allocation, GPUs, Object-oriented Programming, SIMD, Single-Instruction Multiple-Objects, Structure of Arrays | |
| Seminar: | Special Issue of the 33rd European Conference on Object-Oriented Programming (ECOOP 2019) | |
| Related Scholarly Article: | https://dx.doi.org/10.4230/LIPIcs.ECOOP.2019.17 | |
| Issue date: | 2019 | |
| Date of publication: | 12.07.2019 |
