17436

GARDENIA: A Domain-specific Benchmark Suite for Next-generation Accelerators

Zhen Xu, Xuhao Chen, Jie Shen, Yang Zhang, Cheng Chen, Canqun Yang
College of Computer, National University of Defense Technology, Changsha 410073, China
arXiv:1708.04567 [cs.PF], (15 Aug 2017)

@article{xu2017gardenia,

   title={GARDENIA: A Domain-specific Benchmark Suite for Next-generation Accelerators},

   author={Xu, Zhen and Chen, Xuhao and Shen, Jie and Zhang, Yang and Chen, Cheng and Yang, Canqun},

   year={2017},

   month={aug},

   archivePrefix={"arXiv"},

   primaryClass={cs.PF}

}

This paper presents the Graph Analytics Repository for Designing Next-generation Accelerators (GARDENIA), a benchmark suite for studying irregular algorithms on massively parallel accelerators. Existing generic benchmarks for accelerators have mainly focused on high performance computing (HPC) applications with limited control and data irregularity, while available graph analytics benchmarks do not apply state-of-the-art algorithms and/or optimization techniques. GARDENIA includes emerging irregular applications in big-data and machine learning domains which mimic massively multithreaded commercial programs running on modern large-scale datacenters. Our characterization shows that GARDENIA exhibits irregular microarchitectural behavior which is quite different from structured workloads and straightforward-implemented graph benchmarks.
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