{"id":187,"date":"2010-08-18T10:06:35","date_gmt":"2010-08-18T09:06:35","guid":{"rendered":"http:\/\/numbercrunch.de\/blog\/?p=187"},"modified":"2015-08-27T15:58:06","modified_gmt":"2015-08-27T14:58:06","slug":"gpu-computing-literature","status":"publish","type":"post","link":"https:\/\/www.numbercrunch.de\/blog\/2010\/08\/gpu-computing-literature\/","title":{"rendered":"GPU computing literature"},"content":{"rendered":"

A few days ago, I started to gather a\u00a0 survey on GPU computing literature. The survey is non-exhaustive and has strong bias to computational physics applications. However, it might be useful for other GPU computing enthusiasts as well. Therefore, I publish my survey in this post. The list will be updated from time to time. If you think, I missed some important publication, do not hesitate to contact your humble blog author<\/a>.<\/p>\n

Books and articles with review character<\/h1>\n

\n

<\/a> Rupak Biswas, Leonid Oliker, and Jeffrey Vetter. Revolutionary technologies for acceleration of emerging petascale applications. Parallel Computing<\/em>, 35(3):117-118, 2009. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Wu\u00a0chun Feng and Dinesh Manocha. High-performance computing using accelerators. Parallel Computing<\/em>, 33(10-11):645-647, 2007. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Volodymyr Kindratenko, Robert Wilhelmson, Robert Brunner, Todd\u00a0J. Mart\u00efnez, and Wen mei Hwu. High-performance computing with accelerators. Computing in Science & Engineering<\/em>, 12(4):12-16, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> David Kirk and Wen mei Hwu. Programming Massively Parallel Processors: A Hands-on Approach<\/em>. Morgan Kaufmann, 2010.<\/p>\n

<\/a> J.\u00a0D. Owens, M.\u00a0Houston, D.\u00a0Luebke, S.\u00a0Green, J.\u00a0E. Stone, and J.\u00a0C. Phillips. GPU computing. Proceedings of the IEEE<\/em>, 96(5):879-899, 2008. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Jason Sanders and Edward Kandrot. CUDA by Example: An Introduction to General-Purpose GPU Programming<\/em>. Addison-Wesley Professional, 2010.<\/p>\n

\n

Tools and languages for GPU computing<\/h1>\n

\n

<\/a> Patrick McCormick, Jeff Inman, James Ahrens, Jamaludin Mohd-Yusof, Greg Roth, and Sharen Cummins. Scout: a data-parallel programming language for graphics processors. Parallel Computing<\/em>, 33(10-11):648-662, 2007. [\u00a0DOI<\/a> ]<\/p>\n

\n

Applications of GPU computing in numerical linear algebra and numerical algorithms<\/h1>\n

\n

<\/a> Joseph\u00a0M. Elble, Nikolaos\u00a0V. Sahinidis, and Panagiotis Vouzis. GPU computing with Kaczmarz’s and other iterative algorithms for linear systems. Parallel Computing<\/em>, 36(5-6):215-231, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Dominik G\u00f6ddeke, Robert Strzodka, Jamaludin Mohd-Yusof, Patrick McCormick, Sven H.\u00a0M. Buijssen, Matthias Grajewski, and Stefan Turek. Exploring weak scalability for FEM calculations on a GPU-enhanced cluster. Parallel Computing<\/em>, 33(10-11):685-699, 2007. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Naga\u00a0K. Govindaraju and Dinesh Manocha. Cache-efficient numerical algorithms using graphics hardware. Parallel Computing<\/em>, 33(10-11):663-684, 2007. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Stanimire Tomov, Jack Dongarra, and Marc Baboulin. Towards dense linear algebra for hybrid GPU accelerated manycore systems. Parallel Computing<\/em>, 36(5-6):232-240, 2010. [\u00a0DOI<\/a> ]<\/p>\n

\n

Applications of GPU computing in discrete mathematics<\/h1>\n

\n

<\/a> AydIn Bulu\u00e7, John\u00a0R. Gilbert, and Ceren Budak. Solving path problems on the GPU. Parallel Computing<\/em>, 36(5-6):241-253, 2010. [\u00a0DOI<\/a> ]<\/p>\n

\n

Applications of GPU computing in physics and natural sciences<\/h1>\n

\n

<\/a> S.\u00a0Bianchi and R.\u00a0Di Leonardo. Real-time optical micro-manipulation using optimized holograms generated on the GPU. Computer Physics Communications<\/em>, 181(8):1444-1448, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Benjamin Block, Peter Virnau, and Tobias Preis. Multi-GPU accelerated multi-spin Monte Carlo simulations of the 2d Ising model. Computer Physics Communications<\/em>, 181(9):1549-1556, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Philip Brown, Christopher\u00a0J. Woods, Simon McIntosh-Smith, and Frederick\u00a0R. Manby. A massively multicore parallelization of the Kohn-Sham energy gradients. Journal of Computational Chemistry<\/em>, 31(10):2008-2013, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Trevor Cickovski, Santanu Chatterjee, Jacob Wenger, Christopher\u00a0R. Sweet, and Jes\u00fas\u00a0A. Izaguirre. MDLab: A molecular dynamics simulation prototyping environment. Journal of Computational Chemistry<\/em>, 31(7):1345-1356, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> M.A. Clark, R.\u00a0Babich, K.\u00a0Barros, R.C. Brower, and C.\u00a0Rebbi. Solving lattice QCD systems of equations using mixed precision solvers on GPUs. Computer Physics Communications<\/em>, 181(9):1517-1528, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Peter Eastman and Vijay Pande. OpenMM: a hardware-independent framework for molecular simulations. Computing in Science & Engineering<\/em>, 12(4):34-39, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Peter Eastman and Vijay\u00a0S. Pande. Efficient nonbonded interactions for molecular dynamics on a graphics processing unit. Journal of Computational Chemistry<\/em>, 31(6):1268-1272, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> R.G. Edgar, M.A. Clark, K.\u00a0Dale, D.A. Mitchell, S.M. Ord, R.B. Wayth, H.\u00a0Pfister, and L.J. Greenhill. Enabling a high throughput real time data pipeline for a large radio telescope array with GPUs. Computer Physics Communications<\/em>, 181(10):1707-1714, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Mark\u00a0S. Friedrichs, Peter Eastman, Vishal Vaidyanathan, Mike Houston, Scott Legrand, Adam\u00a0L. Beberg, Daniel\u00a0L. Ensign, Christopher\u00a0M. Bruns, and Vijay\u00a0S. Pande. Accelerating molecular dynamic simulation on graphics processing units. Journal of Computational Chemistry<\/em>, 30(6):864-872, 2009. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Eladio Guti\u00e9rrez, Sergio Romero, Mar\u00eda\u00a0A. Trenas, and Emilio\u00a0L. Zapata. Quantum computer simulation using the CUDA programming model. Computer Physics Communications<\/em>, 181(2):282-300, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Imran\u00a0S. Haque and Vijay\u00a0S. Pande. PAPER-accelerating parallel evaluations of ROCS. Journal of Computational Chemistry<\/em>, 31(1):117-132, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> David\u00a0J. Hardy, John\u00a0E. Stone, and Klaus Schulten. Multilevel summation of electrostatic potentials using graphics processing units. Parallel Computing<\/em>, 35(3):164-177, 2009. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> M.\u00a0Januszewski and M.\u00a0Kostur. Accelerating numerical solution of stochastic differential equations with CUDA. Computer Physics Communications<\/em>, 181(1):183-188, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> F.\u00a0Moln\u00e1r Jr., T.\u00a0Szak\u00e1ly, R.\u00a0M\u00e9sz\u00e1ros, and I.\u00a0Lagzi. Air pollution modelling using a graphics processing unit with CUDA. Computer Physics Communications<\/em>, 181(1):105-112, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Rory Kelly. GPU computing for atmospheric modeling. Computing in Science & Engineering<\/em>, 12(4):26-33, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Gaurav Khanna and Justin McKennon. Numerical modeling of gravitational wave sources accelerated by OpenCL. Computer Physics Communications<\/em>, 181(9):1605-1611, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Dimitri Komatitsch, Gordon Erlebacher, Dominik G\u00f6ddeke, and David Mich\u00e9a. High-order finite-element seismic wave propagation modeling with MPI on a large GPU cluster. Journal of Computational Physics<\/em>, 229(20):7692-7714, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Edgar Luttmann, Daniel\u00a0L. Ensign, Vishal Vaidyanathan, Mike Houston, Noam Rimon, Jeppe \u00d8land\u00a0Guha Jayachandran, Mark Friedrichs, and Vijay\u00a0S. Pande. Accelerating molecular dynamic simulation on the cell processor and playstation\u00a03. Journal of Computational Chemistry<\/em>, 30(2):268-274, 2009. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Paul Martinsen, Johannes Blaschke, Rainer K\u00fcnnemeyer, and Robert Jordan. Accelerating Monte Carlo simulations with an NVIDIA graphics processor. Computer Physics Communications<\/em>, pages 1983-1989, 2009. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Jeremy\u00a0S. Meredith, Gonzalo Alvarez, Thomas\u00a0A. Maier, Thomas\u00a0C. Schulthess, and Jeffrey\u00a0S. Vetter. Accuracy and performance of graphics processors: A quantum Monte Carlo application case study. Parallel Computing<\/em>, 35(3), 2009. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Tetsu Narumi, Kenji Yasuoka, Makoto Taiji, and Siegfried H\u00f6finger. Current performance gains from utilizing the GPU or the ASIC MDGRAPE-3 within an enhanced Poisson Boltzmann approach. Journal of Computational Chemistry<\/em>, 30(14):2351-2357, 2009. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Adrian Pope, Salman Habib, Zarija Luki\u0107, David Daniel, Patricia Fasel, Nehal Desai, and Katrin Heitmann. The accelerated universe. Computing in Science & Engineering<\/em>, 12(4):17-25, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Tobias Preis, Peter Virnau, Wolfgang Paul, and Johannes\u00a0J. Schneider. GPU accelerated Monte Carlo simulation of the 2d and 3d ising model. Journal of Computational Physics<\/em>, 228(12):4468-4477, 2009. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Diego Rossinelli, Michael Bergdorf, Georges-Henri Cottet, and Petros Koumoutsakos. GPU accelerated simulations of bluff body flows using vortex particle methods. Journal of Computational Physics<\/em>, 229:3316-3333, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> J.\u00a0Sainio. CUDAEASY – a GPU accelerated cosmological lattice program. Computer Physics Communications<\/em>, 181(5):906-912, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Nathan Schmid, Mathias B\u00f6tschi, and Wilfred F.\u00a0Van Gunsteren. A GPU solvent-solvent interaction calculation accelerator for biomolecular simulations using the GROMOS software. Journal of Computational Chemistry<\/em>, 31(8):1636-1643, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> John\u00a0E. Stone, James\u00a0C. Phillips, Peter\u00a0L. Freddolino, David\u00a0J. Hardy, Leonardo\u00a0G. Trabuco, and Klaus Schulten. Accelerating molecular modeling applications with graphics processors. Journal of Computational Chemistry<\/em>, 28(16):2618-2640, 2007. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Alfeus Sunarso, Tomohiro Tsuji, and Shigeomi Chono. GPU-accelerated molecular dynamics simulation for study of liquid crystalline flows. Journal of Computational Physics<\/em>, 229(15):5486-5497, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Cole Trapnell and Michael\u00a0C. Schatz. Optimizing data intensive GPGPU computations for DNA sequence alignment. Parallel Computing<\/em>, 35(8-9):429-440, 2009. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Mark Watson, Roberto Olivares-Amaya, Richard\u00a0G. Edgar, and Alan Aspuru-Guzik. Accelerating correlated quantum chemistry calculations using graphical processing units. Computing in Science & Engineering<\/em>, 12(4):40-50, 2010. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> Koji Yasuda. Two-electron integral evaluation on the graphics processor unit. Journal of Computational Chemistry<\/em>, 29(3):334-342, 2008. [\u00a0DOI<\/a> ]<\/p>\n

<\/a> R.\u00a0Yokota, T.\u00a0Narumi, R.\u00a0Sakamaki, S.\u00a0Kameoka, S.\u00a0Obi, and K.\u00a0Yasuoka. Fast multipole methods on a cluster of GPUs for the meshless simulation of turbulence. Computer Physics Communications<\/em>, 180(11), 2009. [\u00a0DOI<\/a> ]<\/p>\n

\n

Applications of GPU computing in imaging and visualization<\/h1>\n

\n

<\/a> Yusuke Okitsu, Fumihiko Ino, and Kenichi Hagihara. High-performance cone beam reconstruction using CUDA compatible GPUs. Parallel Computing<\/em>, 36(2-3):129-141, 2010. [\u00a0DOI<\/a> ]<\/p>\n

\n

Applications of GPU computing in finance<\/h1>\n

\n

<\/a> Vladimir Surkov. Parallel option pricing with Fourier space time-stepping method on graphics processing units. Parallel Computing<\/em>, 36(7):372-380, 2010. [\u00a0DOI<\/a> ]<\/p>\n

\n","protected":false},"excerpt":{"rendered":"

A few days ago, I started to gather a\u00a0 survey on GPU computing literature. The survey is non-exhaustive and has strong bias to computational physics applications. However, it might be useful for other GPU computing enthusiasts as well. Therefore, I publish my survey in this post. 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