PPT-Introduction to CUDA

Author : alexa-scheidler | Published Date : 2015-09-22

heterogeneous programming Katia Oleinik koleinikbuedu Scientific Computing and Visualization Boston University Architecture NVIDIA Tesla M2070 Core clock 115GHz

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Introduction to CUDA: Transcript

heterogeneous programming Katia Oleinik koleinikbuedu Scientific Computing and Visualization Boston University Architecture NVIDIA Tesla M2070 Core clock 115GHz Single instruction 448 CUDA cores . Basically a child CUDA Kernel can be called from within a parent CUDA kernel and then optionally synchronize on the completion of that child CUDA Kernel The parent CUDA kernel can consume the output produced from the child CUDA Kernel all withou t . 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. CUDA Platform. CUDA Parallel Computing Platform. . Hardware . . . Capabilities. GPUDirect. SMX. Dynamic Parallelism. HyperQ. Programming . Approaches. Libraries. “Drop-in” Acceleration. © Dan Negrut, . 2012. UW-Madison. Dan Negrut. Simulation-Based Engineering Lab. Wisconsin Applied Computing Center. Department of Mechanical Engineering. Department of . Electrical and Computer Engineering. 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. 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). heterogeneous programming. Brian Gregor. bgregor@bu.edu. Research Computing Services. Boston University. CUDA C/C BASICS. NVIDIA . Corporation. © NVIDIA 2013. What is CUDA?. CUDA Architecture. Expose GPU parallelism for general-purpose computing. Introduction to CUDA Programming CUDA Programming Introduction Andreas Moshovos Winter 2009 Some slides/material from: UIUC course by Wen-Mei Hwu and David Kirk UCSB course by Andrea Di Blas Universitat Jena by Waqar Saleem What is CUDA?. Data Parallelism. Host-Device model. Thread execution. Matrix-multiplication . GPU revised!. What is CUDA?. C. ompute . D. evice . U. nified . A. rchitecture. Programming interface to GPU. CUDA Programming Introduction. Andreas Moshovos. Winter 2009. Some slides/material from:. UIUC course by Wen-Mei Hwu and David Kirk. UCSB course by Andrea Di Blas. Universitat Jena by Waqar Saleem . NVIDIA by Simon Green. Agenda. Text book / resources. Eclipse . Nsight. , NVIDIA Visual Profiler. Available libraries. Questions. Certificate dispersal. (Optional) Multiple GPUs: Where’s Pixel-Waldo?. Text Book / Resources. Cliff Woolley NVIDIADeveloper Technology GroupGPUCPUGPGPU Revolutionizes ComputingLatency Processor Throughput processorLow Latency or High ThroughputCPUOptimized for low-latency access to cached dat

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