7219

Speculative Parallelization on GPGPUs

Min Feng, Rajiv Gupta, Laxmi N. Bhuyan
University of California, Riverside
17th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming (PPoPP), 2012

@article{feng2012speculative,

   title={Speculative Parallelization on GPGPUs},

   author={Feng, M. and Gupta, R. and Bhuyan, L.N.},

   year={2012}

}

Download Download (PDF)   View View   Source Source   

1721

views

This paper overviews the first speculative parallelization technique for GPUs that can exploit parallelism in loops even in the presence of dynamic irregularities that may give rise to cross-iteration dependences. The execution of a speculatively parallelized loop consists of five phases: scheduling, computation, misspeculation check, result committing, and misspeculation recovery. We perform misspeculation check on the GPU to minimize its cost. We optimize the procedures of result committing and misspeculation recovery to reduce the result copying and recovery overhead. Finally, the scheduling policies are designed according to the types of cross-iteration dependences to reduce the misspeculation rate. Our preliminary evaluation was conducted on an nVidia Tesla C1060 hosted in an Intel(R) Xeon(R) E5540 machine. We use three benchmarks of which two contain irregular memory accesses and one contain irregular control flows that can give rise to cross-iteration dependences. Our implementation achieves 3.6x-13.8x speedups for loops in these benchmarks.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2024 hgpu.org

All rights belong to the respective authors

Contact us: