PPT-Computing Delaunay Refinement Using the GPU

Feb 26 2017 Zhenghai CHEN Meng QI and Tiow Seng TAN 1 Outline Introduction Literature Review Our Algorithm gQM Proof of Termination Experiment Results 2 Introduction Delaunay refinement problem. Vitkup D., Melamud E., Moult J., Sander C. Completeness in structural genomics. Nature Struct. Biol. 2001;8:559-566.. -Venkatesan Ravichandran,. 657731350. Contents . Introduction. Structural . Alignments. . March 9, 2012. Speaker:. Meng . Qi. co-authors . : . Thanh-Tung . Cao, Tiow-Seng Tan. 1. Outline. Background. Motivation & Algorithm Overview. GPU-CDT. Proof & Analysis. Experiment Results. Maximize agreement with diffraction data. Minimize R-factor. Maximize ideality of stereochemistry. Minimize deviation from ideal bond lengths and angles. S. |F. obs. -F. calc. |. S. |F. obs. |. hkl. hkl. Swanand. Gore & Gerard . Kleywegt. May 6. th. 2010, 12-1 pm. Macromolecular Crystallography Course. Outline. Intuitive idea of resolution – why higher order diffraction is better.. Parameters, model, observations, refinement – more data is better.. Michael Butler. University of Southampton. users.ecs.soton.ac.uk/mjb. Motivation. In a refinement based approach it is beneficial to model systems . abstractly . with . little architectural structure . +. Delaunay Triangulation. Chrissie Waddington. Harry . Moyse. Mesh Generation. Creating a 3d . polyogonal. shape from data. E.g. :. protein structure from microscope. Fancy 3d graphs. Computer games. 2011-09-14. Four levels of programmers. Implementation. know the language well, translate idea to programs. Algorithms. Design good solutions. Software engineering. manage different components and people. Maximize agreement with diffraction data. Minimize R-factor. Maximize ideality of stereochemistry. Minimize deviation from ideal bond lengths and angles. S. |F. obs. -F. calc. |. S. |F. obs. |. hkl. hkl. CS 268 @ Gates 219. October 17, 3:00 – 4:20. Richard Zhang. (for Leo G.). 1. Disclaimer: All figures in the slides are for illustration only. Best approximations were attempted, but preciseness or c. CS 268 @ Gates 219. October 19, 3:00 – 4:20. Richard Zhang. (for Leo G.). 1. Disclaimer: All figures in the slides are for illustration only. Best approximations were attempted, but preciseness or correctness of the geometric constructions should not be assumed.. Add GPUs: Accelerate Science Applications. © NVIDIA 2013. Small Changes, Big Speed-up. Application Code. . GPU. C. PU. Use GPU to Parallelize. Compute-Intensive Functions. Rest of Sequential. CPU Code. Department of Geography and Planning. University at Albany. What is a GPU?. A GPU is a . graphics processing unit. Modern GPUs are composed of multiple processors. Each of these processors can perform operations similar to those of CPUs. CS 179: GPU Programming Lecture 7 Week 3 Goals: Advanced GPU- accelerable algorithms CUDA libraries and tools This Lecture GPU- accelerable algorithms: Reduction Prefix sum Stream compaction Sorting (quicksort) Research Computing Services. Boston . University. GPU Programming. Access to the SCC. Login: . tuta#. Password: . VizTut#. GPU Programming. Access to the SCC GPU nodes. # copy tutorial materials: .