PPT-Texture Memory -in CUDA Perspective

Author : alida-meadow | Published Date : 2018-10-28

TEXTURE MEMORY IN IN CUDA PERSPECTIVE VINAY MANCHIRAJU TEXTURE MEMORY Read only memory used by programs in CUDA Used in General Purpose Computing for Accuracy

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Texture Memory -in CUDA Perspective: Transcript

TEXTURE MEMORY IN IN CUDA PERSPECTIVE VINAY MANCHIRAJU TEXTURE MEMORY Read only memory used by programs in CUDA Used in General Purpose Computing for Accuracy and Efficiency. . Acknowledgement: the lecture materials are based on the materials in NVIDIA teaching center CUDA course materials, including materials from Wisconsin (. Negrut. ), North Carolina Charlotte (. Wikinson. Dr A . Sahu. Dept of Comp Sc & . Engg. . . IIT . Guwahati. 1. Outline. Graphics System . GPU Architecture. Memory Model. Vertex Buffer, Texture buffer. GPU Programming Model. DirectX. , OpenGL, . Håkon Kvale . Stensland. iAD-lab, Department for Informatics. Basic 3D Graphics Pipeline. Application. Scene Management. Geometry. Rasterization. Pixel Processing. ROP/FBI/Display. Frame. Buffer. Memory. and Debugging. Shehzan. ArrayFire. Summary. ArrayFire. GPU Programming and CUDA. Debugging and Profiling using CUDA Tools. Memory Coalescing. Shared Memory and Bank Conflicts. Transpose. Reduction. ArrayFire. Introduction to Programming Massively Parallel Graphics processors. Andreas . Moshovos. moshovos@eecg.toronto.edu. ECE, Univ. of Toronto. Summer 2010. Some slides/material from:. UIUC course by . Wen. Håkon Kvale . Stensland. Simula Research Laboratory. PC Graphics Timeline. Challenges. :. Render infinitely complex scenes. And extremely high resolution. In 1/60. th. of one second (60 frames per second). introduce the use of multiple CUDA streams to overlap memory transfers with kernel computations.. Also introduced is paged-locked memory. 2. Page-locked host memory. (also called pinned host memory). Topics. Non-numerical algorithms. Parallel breadth-first search (BFS). Texture memory. GPUs – good for many numerical calculations…. What about “non-numerical” problems?. Graph Algorithms. Graph Algorithms. Hui. Li. Geoffrey Fox. Research Goal. provide . a uniform . MapReduce programming . model that works . on HPC . Clusters or . Virtual Clusters cores . on traditional Intel architecture chip, cores on . Topics. Non-numerical algorithms. Parallel breadth-first search (BFS). Texture memory. GPUs – good for many numerical calculations…. What about “non-numerical” problems?. Graph Algorithms. Graph Algorithms. Ajaya. . Neupane. , . Zhiyun. Qian . and . Nael. Abu-. Ghazaleh. University of California, Riverside. Rendered Insecure: . GPU Side Channel Attacks . are Practical. 1. G. raphics . P. rocessing . Ajaya. . Neupane. , . Zhiyun. Qian . and . Nael. Abu-. Ghazaleh. University of California, Riverside. Rendered Insecure: . GPU Side Channel Attacks . are Practical. 1. G. raphics . P. rocessing . Cliff Woolley NVIDIADeveloper Technology GroupGPUCPUGPGPU Revolutionizes ComputingLatency Processor Throughput processorLow Latency or High ThroughputCPUOptimized for low-latency access to cached dat May 8-Stephen Jones GTC 2018CUDANEW FEATURESAND BEYOND22CUDA ECOSYSTEM 2018CUDADOWNLOADS IN 20173500000CUDA REGISTERED DEVELOPERS800000GTC ATTENDEES80003CUDA DEVELOPMENT ECOSYSTEMFrom Ease of Use to S

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