PPT-CUDA - 101 Basics Overview

Author : broadcastworld | Published Date : 2020-08-26

What is CUDA Data Parallelism HostDevice model Thread execution Matrixmultiplication GPU revised What is CUDA C ompute D evice U nified A rchitecture Programming

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CUDA - 101 Basics Overview: Transcript

What is CUDA Data Parallelism HostDevice model Thread execution Matrixmultiplication GPU revised What is CUDA C ompute D evice U nified A rchitecture Programming interface to GPU. CUDA Simulation. Benjy. Kessler. Given a brittle substance with a crack in it.. The goal is to study how the crack propagates in the substance as a function of time.. This accomplished by simulating the substance as a grid of points with forces acting upon them.. Washington 101 101 104 20 20 20 525 20 20 5 5 532 526 104 303 305 3 104 405 520 405 18 5 163 16 16 160 7 5 101 101 3 8 108 19 531 17 2 525 167 302 3 5 106 101 11 1191HoodBainbridgeIslandVashonIslandH © 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. Sathish. . Vadhiyar. Parallel Programming. GPU. Graphical Processing Unit. A single GPU consists of large number of cores – hundreds of cores.. Whereas a single CPU can consist of 2, 4, 8 or 12 cores. Overview. GPU Ocelot overview. Building, configuring, and executing Ocelot programs. Ocelot Device Interface and CUDA Runtime API. Ocelot PTX Internal Representation. PTX Pass Manager. 2. Ocelot: Multiplatform Dynamic Compilation. Performance considerations. (CUDA best practices) . NVIDIA CUDA C programming best practices guide. ACK: CUDA teaching center Stanford (. Hoberrock. and . Tarjan. ).. Outline. Host to device memory transfer. 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). ITS Research Computing. Mark Reed . Objectives. Learn why computing with accelerators is important. Understand accelerator hardware. Learn what types of problems are suitable for accelerators. Survey the programming models available. Cliff Woolley NVIDIADeveloper Technology GroupGPUCPUGPGPU Revolutionizes ComputingLatency Processor Throughput processorLow Latency or High ThroughputCPUOptimized for low-latency access to cached dat #Certification #Dumps #Certification_exam_Dumps
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