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Globally scheduled real-time multiprocessor systems with GPUs

Glenn A. Elliott, James H. Anderson
Department of Computer Science, University of North Carolina at Chapel Hill
Real-Time Systems, Volume 48, Number 1, 34-74, 2012

@article{elliott2012globally,

   title={Globally scheduled real-time multiprocessor systems with GPUs},

   author={Elliott, G.A. and Anderson, J.H.},

   journal={Real-Time Systems},

   pages={1–41},

   year={2012},

   publisher={Springer}

}

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Graphics processing units, GPUs, are powerful processors that can offer significant performance advantages over traditional CPUs. The last decade has seen rapid advancement in GPU computational power and generality. Recent technologies make it possible to use GPUs as co-processors to CPUs. The performance advantages of GPUs can be great, often outperforming traditional CPUs by orders of magnitude. While the motivations for developing systems with GPUs are clear, little research in the real-time systems field has been done to integrate GPUs into real-time multiprocessor systems. We present two real-time analysis methods, addressing real-world platform constraints, for such an integration into a soft real-time multiprocessor system and show that a GPU can be exploited to achieve greater levels of total system performance.
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