Towards a Distributed GPU-Accelerated Matrix Inversion
暂无分享,去创建一个
[1] Robert A. van de Geijn,et al. The science of deriving dense linear algebra algorithms , 2005, TOMS.
[2] James Demmel,et al. LU, QR and Cholesky Factorizations using Vector Capabilities of GPUs , 2008 .
[3] Jack Dongarra,et al. ScaLAPACK: a scalable linear algebra library for distributed memory concurrent computers , 1992, [Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation.
[4] B. Tapley,et al. Statistical Orbit Determination , 2004 .
[5] J. D. Roberts,et al. Linear model reduction and solution of the algebraic Riccati equation by use of the sign function , 1980 .
[6] Alexandros V. Gerbessiotis,et al. Programming Research Group ALGORITHMIC AND PRACTICAL CONSIDERATIONS FOR DENSE MATRIX COMPUTATIONS ON THE BSP MODEL , 1997 .
[7] Enrique S. Quintana-Ortí,et al. High Performance Matrix Inversion on a Multi-core Platform with Several GPUs , 2011, 2011 19th International Euromicro Conference on Parallel, Distributed and Network-Based Processing.
[8] Enrique S. Quintana-Ortí,et al. Exploiting the capabilities of modern GPUs for dense matrix computations , 2009, Concurr. Comput. Pract. Exp..
[9] Eduardo Fernández,et al. Inverse lighting design for interior buildings integrating natural and artificial sources , 2012, Comput. Graph..
[10] Robert A. van de Geijn,et al. A Note On Parallel Matrix Inversion , 2000, SIAM J. Sci. Comput..
[11] Mei Han An,et al. accuracy and stability of numerical algorithms , 1991 .
[12] Enrique S. Quintana-Ortí,et al. Matrix inversion on CPU–GPU platforms with applications in control theory , 2013, Concurr. Comput. Pract. Exp..
[13] Enrique S. Quintana-Ortí,et al. Using Hybrid CPU-GPU Platforms to Accelerate the Computation of the Matrix Sign Function , 2009, Euro-Par Workshops.
[14] Robert A. van de Geijn,et al. FLAME: Formal Linear Algebra Methods Environment , 2001, TOMS.