Chanyoung Oh
Xipeng Shen
Jidong Zhai
ABSTRACT
Recent studies have shown promising performance benefits of pipelined stencil applications. An important factor for the computing efficiency of such pipelines is the granularity of a task. We presents GOPipe, the first granularity-oblivious programming framework for efficient pipelined stencil executions. With GOPipe, programmers no longer need to specify the appropriate task granularity. GOPipe automatically finds it, and schedules tasks of that granularity while observing all inter-task and inter-stage data dependencies. In our experiments on four real-life applications, GOPipe outperforms the state-of-the-art by up to 4.57× with a much better programming productivity.
- Markus Steinberger, Michael Kenzel, Pedro Boechat, Bernhard Kerbl, Mark Dokter, and Dieter Schmalstieg. 2014. Whippletree: Task-based Scheduling of Dynamic Workloads on the GPU. ACM Transactions on Graphics 33, 6 (2014), 1--11. Google Scholar
Digital Library
- Zhen Zheng, Chanyoung Oh, Jidong Zhai, Xipeng Shen, Youngmin Yi, and Wenguang Chen. 2017. VersaPipe: A Versatile Programming Framework for Pipelined Computing on GPU. In Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO-50). Cambridge, MA, USA, 587--599. Google ScholarDigital Library
Index Terms
- GOPipe: a granularity-oblivious programming framework for pipelined stencil executions on GPU
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