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A Programming Model for GPU Load Balancing

Muhammad Osama, Serban D. Porumbescu, John D. Owens
University of California, Davis, California, USA
arXiv:2301.04792 [cs.DC], (12 Jan 2023)

@article{osama2023programming,

   title={A Programming Model for GPU Load Balancing},

   author={Osama, Muhammad and Porumbescu, Serban D. and Owens, John D.},

   year={2023}

}

We propose a GPU fine-grained load-balancing abstraction that decouples load balancing from work processing and aims to support both static and dynamic schedules with a programmable interface to implement new load-balancing schedules. Prior to our work, the only way to unleash the GPU’s potential on irregular problems has been to workload-balance through application-specific, tightly coupled load-balancing techniques. With our open-source framework for load-balancing, we hope to improve programmers’ productivity when developing irregular-parallel algorithms on the GPU, and also improve the overall performance characteristics for such applications by allowing a quick path to experimentation with a variety of existing load-balancing techniques. Consequently, we also hope that by separating the concerns of load-balancing from work processing within our abstraction, managing and extending existing code to future architectures becomes easier.
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