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Task Scheduling of Parallel Processing in CPU-GPU Collaborative Environment

Lei Wang, Yong-Zhong Huang, Xin Chen, Chun-Yan Zhang
Zhengzhou Inf. Sci. & Technol. Inst., Zhengzhou
2008 International Conference on Computer Science and Information Technology (2008) Publisher: Ieee, Pages: 228-232

@conference{wang2008task,

   title={Task Scheduling of Parallel Processing in CPU-GPU Collaborative Environment},

   author={Wang, L. and Huang, Y. and Chen, X. and Zhang, C.},

   booktitle={Computer Science and Information Technology, 2008. ICCSIT’08. International Conference on},

   pages={228–232},

   year={2008},

   organization={IEEE}

}

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With the rapid development of GPU (Graphics Processor Unit) in recent years, GPGPU (General-Purpose computation on GPU) has become an important technique in scientific research. However GPU might well be seen more as a cooperator than a rival to CPU. Therefore, we focus on exploiting the power of CPU and GPU in solving generic problems based on collaborative and heterogeneous computing environment. In this work we present a parallel processing paradigm based on CPU-GPU collaborative computing model to optimize the performance of task schediding. In addition, we evaluate a new task scheduling algorithm using NVIDIA GeForce 7600GT compare with traditional task scheduling algorithm. The results show that our algorithm increase average performance of 26.5% compared with traditional algorithm. Based on our results and current trends in microarchitecture, we believe that efficient use of CPU-GPU collaborative environment will become increasingly important to high-performance computing.
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