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DynaSOAr: A Parallel Memory Allocator for Object-Oriented Programming on GPUs with Efficient Memory Access (Artifact)

Authors Matthias Springer, Hidehiko Masuhara

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DARTS.5.2.2.pdf
  • Filesize: 291 kB
  • 2 pages

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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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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.

Cite As Get 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

Author Details

Matthias Springer
  • Tokyo Institute of Technology, Japan
Hidehiko Masuhara
  • Tokyo Institute of Technology, Japan

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.

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  MD5 Sum: e7b8bb33961ae66209581e2c58c6cad3 (Get MD5 Sum)

Related Article

  • Matthias Springer and Hidehiko Masuhara, "DynaSOAr: A Parallel Memory Allocator for Object-Oriented Programming on GPUs with Efficient Memory Access", in 33rd European Conference on Object-Oriented Programming (ECOOP 2019), LIPIcs, Vol. 134, pp. 17:1 - 17:37, 2019. https://dx.doi.org/10.4230/LIPIcs.ECOOP.2019.17
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