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Open Access Publications from the University of California

Mini-Gunrock: A Lightweight Graph Analytics Framework on the GPU

  • Author(s): Wang, Yangzihao
  • Baxter, Sean
  • Owens, John D.
  • et al.

Existing GPU graph analytics frameworks are typically built from specialized, bottom-up implementations of graph operators that are customized to graph computation. In this work we describe Mini-Gunrock, a lightweight graph analytics framework on the GPU. Unlike existing frameworks, Mini-Gunrock is built from graph operators implemented with generic transform-based data-parallel primitives. Using this method to bridge the gap between programmability and high performance for GPU graph analytics, we demonstrate operator performance on scale-free graphs with an average 1.5x speedup compared to Gunrock’s corresponding operator performance. Mini-Gunrock’s graph operators, optimizations, and applications code have 10x smaller code size and comparable overall performance vs. Gunrock.

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