Sparse Cholesky factorizations in CUDA

Question

As the CUDA programming model matures, I wonder if anyone is aware of any available research code or open-source libraries that implement sparse Cholesky factorizations on NVIDIA GPUs.

On May 2012, I 've been pointed to the following literature by V. Volkov

[1] Christen et al., 2007 General-Purpose Sparse Matrix Building Blocks using the NVIDIA CUDA Technology Platform, http://www.cs.jhu.edu/~misha/ReadingSeminar/Papers/Christen07.pdf

[2] Krawezik and Poole, 2009, Accelerating the ANSYS Direct Sparse Solver with GPUs, http://saahpc.ncsa.illinois.edu/09/papers/Krawezik_paper.pdf

[3] Yu et al., 2011, A CPU-GPU hybrid approach for the unsymmetric multifrontal method, http://www.sciencedirect.com/science/article/pii/S0167819111001293

[4] George et al., 2011, Multifrontal Factorization of Sparse SPD Matrices on GPUs, http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6012808

[5] Lucas et al., 2012, Multifrontal Sparse Matrix Factorization on Graphics Processing Units, ftp://ftp.isi.edu/isi-pubs/tr-677.pdf

Answer 1

Tim Davis work suitesparse and nVIDIA's acceleration cusparse. AMD might support Cholesky decomposition in the near future.