cse3431-lecture13-raytracing Z-buffer algorithm for each polygon in model project vertices of polygon onto viewing plane for each pixel inside the projected polygon calculate pixel colour calculate pixel z-value compare pixel z-value to value stored for pixel in z-buffer if pixel is closer, draw it in frame-buffer and z-buffer end end Z-buffer Graphics Pipeline Modeling […]
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COMP8551 Heterogenous computing COMP 8551 Advanced Games Programming Techniques Heterogenous computing Borna Noureddin, Ph.D. British Columbia Institute of Technology Overview •Motivation •Parallel software •Data-parallel • Task-parallel •Heterogenous computing 2 © B or na N ou re dd in C O M P 85 51 Motivation • Programming computers composed of a combination of CPUs, GPUs,
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PowerPoint Presentation Parallel Computing with GPUs: Warp Level CUDA and Atomics Dr Paul Richmond http://paulrichmond.shef.ac.uk/teaching/COM4521/ Last Teaching Week We learnt about shared memory Very powerful for block level computations Excellent for improving performance by reducing memory bandwidth User controlled caching and needs careful consideration for bank conflicts and boundary conditions Memory coalescing: Vital for good
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Com 4521 Parallel Computing with GPUs: Lab 04 Spring Semester 2018 Dr Paul Richmond Lab Assistants: Robert Chisholm, John Charlton Department of Computer Science, University of Sheffield Learning Outcomes Understand how to launch CUDA kernels Understand and demonstrate how to allocate and move memory to and from the GPU Understand CUDA thread
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University of Toronto, Department of Computer Science CSC 485/2501F—Computational Linguistics, Fall 2018 Assignment 3 Due date: 23:59, Thursday 6 December 2018, at the course drop-box in BA 2220. Late assignments will not be accepted without a valid medical certificate or other documentation of an emergency. This assignment is worth either 25% (CSC 2501) or 33%
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Microsoft PowerPoint – 1-fundamentals-1 [Compatibility Mode] 27Computer Science, University of Warwick Related Technologies •HPC covers a wide range of technologies: • Computer architecture • Networking • Compilers • Algorithms • Workload and resource manager • A big HPC system handles many parallel programs from different users • Task scheduling and resource allocation • metrics: system
Computer Organization and Design: The Hardware/Software Interface In Praise of Computer Organization and Design: The Hardware/ Software Interface, Fifth Edition “Textbook selection is oft en a frustrating act of compromise—pedagogy, content coverage, quality of exposition, level of rigor, cost. Computer Organization and Design is the rare book that hits all the right notes across the
PowerPoint Presentation Parallel Computing with GPUs: Shared Memory Dr Paul Richmond http://paulrichmond.shef.ac.uk/teaching/COM4521/ Average Mark: 71% Grids, Blocks, Warps & Threads Grid Block Thread GPU SM SM SMSM Device Memory Shared Memory / Local Cache 32 CUDA core partitions – execute warps Grids, Blocks, Warps & Threads Blocks map to SMs SMs may have more than
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PowerPoint Presentation Graphics Systems The slides adapted in part courtesy of Angel’s Interactive Computer Graphics 6E © Addison-Wesley 2012. Computer Graphics Instructor: Sungkil Lee 2 Today • Image formation • Two basic approaches of graphics systems • Physical approach • Pipeline approach 3 Image Formation • Geometry of image formation • determines where the projection
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Computer Organization and Design: The Hardware/Software Interface In Praise of Computer Organization and Design: The Hardware/ Software Interface, Fifth Edition “Textbook selection is oft en a frustrating act of compromise—pedagogy, content coverage, quality of exposition, level of rigor, cost. Computer Organization and Design is the rare book that hits all the right notes across the