programaciÓn en el entorno cuda en aplicaciones de...
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PROGRAMACIÓN EN EL ENTORNO CUDA EN APLICACIONES DE MECÁNICA COMPUTACIONAL.
BIBLIOGRAFÍA
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BIBLIOGRAFÍA:
Métodos Numéricos:
Méthodes Numériques: Algorithmes, analyse et applications.
Alfio Quarteroni, Riccardo Sacco et Fausto Saleri. Ed Springer 2007
Iterative Methods for Sparse Linear Systems.
Youssef SAAD. 2000
Templates for the Solution of Linear Systems:
Building Blocks for Iterative Methods
Richard Barrett, Michael Berry, Tony F. Chan, James Demme, June M.
Donato, Jack Dongarra, Victor Eijkhout, Roldan Pozo, Charles Romine,
and Henk Van der Vorst
An Introduction to the Conjugate Gradient Method Without the Agonizing
Pain
Edition 1 ¼ Jonathan Richard Shewchuk
Methods of Conjugate Gradients for Solving Linear Systems1
Magnus R. Hestenes and Eduard Stiefel
Bi-cgstab : A fast and smoothly converging variant of bi-cg for the
solution of nonsymmetric linear systems.
H. A. van der Vorst. SIAM Journal on Scientific and Statistical
Computing, 13(2) :631–644, 1992.
Precisión en coma flotante.
IEEE 754-2008 Standard for Floating-Point Arithmetic.
Goldberg, David (1991). "What Every Computer Scientist Should Know
About Floating-Point Arithmetic". Goldberg, David (1991). ACM
Computing Surveys 23: 5–48.
PROGRAMACIÓN EN EL ENTORNO CUDA EN APLICACIONES DE MECÁNICA COMPUTACIONAL.
BIBLIOGRAFÍA
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Lenguaje de programación C:
The C Programming Language.
B.W. Kernighan and D.M. Ritchie.
CUDA de NVIDIA:
CUBLAS_Library_3.0
CUFFT_Library_3.1
NVIDIA_CUDA_BestPracticesGuide_2.3
NVIDIA_CUDA_Programming_Guide_2.3
CUDA_Getting_Started_2.3_Linux
NVIDIA_CUDA_BestPracticesGuide_2.3
CUDA_Reference_Manual_2.3
NVIDIA_Fermi_Compute_Architecture_Whitepaper
Catálogos de productos NVIDIA.
Apuntes CUDA:
CUDA University Course, University of Illinois : ECE 498AL
Professor Wen-mei W. Hwu and David Kirk,
SpMV en CUDA:
Efficient sparse matrix-vector multiplication on CUDA. NVIDIA.
Technical Report NVR-2008-004, Nathan Bell and Michael Garland. NVIDIA
Corporation, December 2008.
Implementing Sparse Matrix-Vector Multiplication on Throughput-
Oriented Processors.
Nathan Bell and Michael Garland.
PROGRAMACIÓN EN EL ENTORNO CUDA EN APLICACIONES DE MECÁNICA COMPUTACIONAL.
BIBLIOGRAFÍA
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Artículos sobre resolución de sistemas lineales usando tecnología GPU:
Implementation of a Lattice-Boltzmann-Method for numerical Fluid
Mechanics using the nVidia CUDA Technology
Eugen Riegel & Thomas Indinger
Optimization of FTLE Calculations Using nVidia's CUDA
Raymond Jimenez and Joris Vankerschavery
CUDA kernel for conjugate gradient in lattice QCD
Kenji Ogawa
WORKSHOP on GPU Supercomputing January 16, 2009 NTU, Taipei
Accelerating Unstructured Mesh Computational Fluid Dynamics on the
NVidia Tesla GPU Architecture
Graham MARKALL
Concurrent number cruncher
A GPU implementation of a general sparse linear solver
Luc Buatois, Guillaume Caumon and Bruno Lévy
CFD-based analysis and two-level aerodynamic optimization on graphics
processing units
I.C. Kampolis, X.S. Trompoukis, V.G. Asouti, K.C. Giannakoglou
Solving Lattice QCD systems of equations using mixed precision solvers
on GPUs
M. A. Clarka, R. Babichc, K. Barrose, R. C. Browerc, C. Rebbic
Solving Sparse Linear Systems on NVIDIA Tesla GPUs∗ Mingliang Wang, Hector Klie, Manish Parashar, and Hari Sudan
PROGRAMACIÓN EN EL ENTORNO CUDA EN APLICACIONES DE MECÁNICA COMPUTACIONAL.
BIBLIOGRAFÍA
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Webs :
http://gpgpu.org/
http://math.nist.gov/MatrixMarket/
http://www.netlib.org/blas/
http://www.netlib.org/lapack/
http://www.cplusplus.com/
http://www.cprogramming.com/tutorial.html
http://code.google.com/p/cusp-library/
http://code.google.com/p/thrust/