4226

Sparse matrix computations on manycore GPU’s

Michael Garland
NVIDIA Corporation, Santa Clara, CA
45th ACM/IEEE Design Automation Conference, 2008. DAC 2008

@inproceedings{garland2008sparse,

   title={Sparse matrix computations on manycore GPU’s},

   author={Garland, M.},

   booktitle={Proceedings of the 45th annual Design Automation Conference},

   pages={2–6},

   year={2008},

   organization={ACM}

}

Source Source   

691

views

Modern microprocessors are becoming increasingly parallel devices, and GPUs are at the leading edge of this trend. Designing parallel algorithms for manycore chips like the GPU can present interesting challenges, particularly for computations on sparse data structures. One particularly common example is the collection of sparse matrix solvers and combinatorial graph algorithms that form the core of many physical simulation techniques. Although seemingly irregular, these operations can often be implemented with data parallel operations that map very well to massively parallel processors.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2017 hgpu.org

All rights belong to the respective authors

Contact us: