PPT-CUDA Profiling

Author : mitsue-stanley | Published Date : 2017-03-31

and Debugging Shehzan ArrayFire Summary ArrayFire GPU Programming and CUDA Debugging and Profiling using CUDA Tools Memory Coalescing Shared Memory and Bank Conflicts

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CUDA Profiling: Transcript

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. 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 heterogeneous programming. Katia Oleinik. koleinik@bu.edu. Scientific Computing and Visualization. Boston . University. Architecture. NVIDIA Tesla M2070: . Core clock: 1.15GHz . Single instruction . 448 CUDA cores . . 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 Kat . Hadjimatheou. Research . Fellow. Dept. . o. f Philosophy. University of Birmingham. Outline. Is . ethnic profiling harder to justify than behavioural profiling . in principle or for contingent . © 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. For Evaluating Error Resilience of GPGPU Applications. Bo . Fang . , . Karthik. . Pattabiraman. , . Matei. . Ripeanu. ,. The . University of British . Columbia. Sudhanva. . Gurumurthi. . AMD Research. Applications. CUDA Course. July 21-25. István. Reguly. Introduction. Why is my application running slow?. Work it out on paper. Instrument code. Profile it. NVIDIA Visual Profiler. Works with CUDA, needs some tweaks to work with . 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). on . Ubuntu. Cuda. download site. . https://developer.nvidia.com/cuda-downloads. $ . sudo. . dpkg. -. i. cuda-repo-ubuntu1404_7.5-18_amd64.deb . $ . sudo. apt-get update . $ . sudo. apt-get install . 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). 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. 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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