DARTS.5.2.2.pdf
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DynaSOAr: A Parallel Memory Allocator for Object-Oriented Programming on GPUs with Efficient Memory Access (Artifact)
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Part of:
Issue:
Special Issue of the 33rd European Conference on Object-Oriented Programming (ECOOP 2019)
Volume: DARTS, Volume 5 (ECOOP 2019)
Conference: European Conference on Object-Oriented Programming (ECOOP)
Journal: Dagstuhl Artifacts Series (DARTS) - License:
Creative Commons Attribution 3.0 Germany license
- Publication Date: 2019-07-12
Artifact Description
Document Identifiers
Acknowledgements
This work was supported by a JSPS Research Fellowship for Young Scientists (KAKENHI Grant Number 18J14726). We gratefully acknowledge the support of NVIDIA Corporation with the donation of the TITAN Xp GPU used for this research.
Cite AsGet BibTex
Matthias Springer and Hidehiko Masuhara. DynaSOAr: A Parallel Memory Allocator for Object-Oriented Programming on GPUs with Efficient Memory Access (Artifact). In Special Issue of the 33rd European Conference on Object-Oriented Programming (ECOOP 2019). Dagstuhl Artifacts Series (DARTS), Volume 5, Issue 2, pp. 2:1-2:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/DARTS.5.2.2
https://doi.org/10.4230/DARTS.5.2.2
Artifact
DARTS-5-2-2-artifact-e7b8bb33961ae66209581e2c58c6cad3.zip
(Filesize: 2.9 MB)
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.
Subject Classification
ACM Subject Classification
- Software and its engineering → Allocation / deallocation strategies
- Software and its engineering → Object oriented languages
- Computer systems organization → Single instruction, multiple data
Keywords
- CUDA
- Data Layout
- Dynamic Memory Allocation
- GPUs
- Object-oriented Programming
- SIMD
- Single-Instruction Multiple-Objects
- Structure of Arrays
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