Concurrent CPU-GPU Task Programming using Modern C++
Department of Electrical and Computer Engineering, University of Utah
arXiv:2203.08395 [cs.DC], (16 Mar 2022)
@article{huang2022concurrent,
title={Concurrent CPU-GPU Task Programming using Modern C++},
author={Huang, Tsung-Wei and Lin, Yibo},
year={2022}
}
In this paper, we introduce Heteroflow, a new C++ library to help developers quickly write parallel CPU-GPU programs using task dependency graphs. Heteroflow leverages the power of modern C++ and task-based approaches to enable efficient implementations of heterogeneous decomposition strategies. Our new CPU-GPU programming model allows users to express a problem in a way that adapts to effective separation of concerns and expertise encapsulation. Compared with existing libraries, Heteroflow is more cost-efficient in performance scaling, programming productivity, and solution generality. We have evaluated Heteroflow on two real applications in VLSI design automation and demonstrated the performance scalability across different CPU-GPU numbers and problem sizes. At a particular example of VLSI timing analysis with million-scale tasking, Heteroflow achieved 7.7x runtime speed-up (99 vs 13 minutes) over a baseline on a machine of 40 CPU cores and 4 GPUs.
March 20, 2022 by hgpu
