18539

SoaAlloc: Accelerating Single-Method Multiple-Objects Applications on GPUs

Matthias Springer
Tokyo Institute of Technology, Japan
arXiv:1809.07444 [cs.PL], (20 Sep 2018)

@article{springer2018soaalloc,

   title={SoaAlloc: Accelerating Single-Method Multiple-Objects Applications on GPUs},

   author={Springer, Matthias},

   year={2018},

   month={sep},

   archivePrefix={"arXiv"},

   primaryClass={cs.PL}

}

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We propose SoaAlloc, a dynamic object allocator for Single-Method Multiple-Objects applications in CUDA. SoaAlloc is the first allocator for GPUs that (a) arranges allocations in a SIMD-friendly Structure of Arrays (SOA) data layout, (b) provides a do-all operation for maximizing the benefit of SOA, and (c) is on par with state-of-the-art memory allocators for raw (de)allocation time. Our benchmarks show that the SOA layout leads to significantly better memory bandwidth utilization, resulting in a 2x speedup of application code.
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