A control-structure splitting optimization for GPGPU

Snaider Carrillo, Jakob Siegel, Xiaoming Li
University of Delaware, Newark, USA
In CF ’09: Proceedings of the 6th ACM conference on Computing frontiers (2009), pp. 147-150.


   title={A control-structure splitting optimization for GPGPU},

   author={Carrillo, S. and Siegel, J. and Li, X.},

   booktitle={Proceedings of the 6th ACM conference on Computing frontiers},





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Control statements in a GPU program such as loops and branches pose serious challenges for the efficient usage of GPU resources because those control statements will lead to the serialization of threads and consequently ruin the occupancy of GPU, that is, the number of threads running concurrently. Unlike traditional vector processing units that are inside a general purpose processor, the GPU cannot leave the control statements to the CPU because fine-grain statement scheduling between GPU and CPU is impossible. We need an effective method to handle the control statements "just in place" on the GPUs.
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