GPU ACCELERATED PERFORMANCE FORTODAY’S VIRTUAL ArcGIS WORKSPACESOrange Zhan, Virtual GPU Business Lead ASEAN
THE EVOLUTION OF MODERN WORKFLOWSVISUALWORKSPACEMOBILITYInformation Workers/StudentsCOLLABORATIONLARGE DATAINTERACTIVEHPCVRVISUAL COMPUTING SPECTRUMPHOTOREALISMAIDesigners/Scientists2
QUADRO VIRTUAL GPU POWERING THE MOST ADVANCED WORKFLOWSPhotorealistic. Immersive. Collaborative.Media & EntertainmentManufacturing & DesignAECGeospatial, Oil & GasVisual Simulation3
ArcGIS PRO 2.0Highest graphics requirement of any version to date
ESRI ArcGIS PRORole of vGPURENDERINGANALYTIC GEOPROCESSINGDEEP LEARNING
RENDERINGDirectX or OpenGL6
SPATIAL ANALYSTASPECTSLOPEIdentifies the compass directionthat the downhill slope faces foreach location.Identifies the steepness at eachcell of a raster surface. Thelower the slope value, theflatter the terrain; the higher theslope value, the steeper theterrain.VIEWSHEDDetermines surface locationsvisible to a set of point orpolyline observers, usinggeodesic methods.Nvidia GPU-enabled Geoprocessing tools7
HOW IT WORKSNVIDIA virtual GPU products deliver a GPU Experience to every Virtual DesktopCPU Only VDIWith NVIDIAVirtual GPUApps and VMsNVIDIA Graphics DriversApps and VMsNVIDIA Virtual GPUHypervisorNVIDIA virtualization softwareHypervisorServerNVIDIA Tesla GPUServer8
NVIDIA GPUs EVERYWHERE140 Servers from more than 30 system vendorsHypervisor InfrastructureHyper-ConvergedInfrastructureHyper ConvergedIndustry Standard ServersBlade ServersBlade ServersPublic Cloud
ENTERPRISE VDI PLANNINGChoosing the right GPU for your use10
QUADRO vDWS GUIDANCEDeep learning, rendering, immersive visualization,and GPGPU compute applicationsTesla V100Tesla P100Largest CAD models, CAE,Photorealistic rendering,Seismic exploration, GPGPU compute 4GB MemoryTesla P40High-End Quadro vDWSLarge/complex CAD models,Seismic exploration, complexDCC effects, 3D Medical Imaging ReconLarge/complex CAD models,Advanced DCC, Medical ImagingMedium size/complexity CAD models,Basic DCC, Medical Imaging, PLMSmall/simple CADmodels, video, EntryPLMTesla P4Entry – Mid Range Quadro vDWSOffice, SketchupPACS/DiagnosticsSchlumberger, Halliburton, DeltaGen, Catia Live RenderingAutoCAD, Revit, InventorAnsys, Abaqus, SimuliaSolidworks, NX, Creo, CatiaAdobe CC Photoshop, IllustratorAdobe CC Premiere Pro, After Effects, Maya, 3ds Max, Nuke, ArcGis Pro
NVIDIA virtual GPU products deliver a GPU Experience to every Virtual Desktop. Server. Hypervisor. Apps and VMs. NVIDIA Graphics Drivers. NVIDIA Virtual GPU. NVIDIA Tesla GPU. NVIDIA virtualization software. CPU Only VDI. With NVIDIA Virtu
OpenCV GPU header file Upload image from CPU to GPU memory Allocate a temp output image on the GPU Process images on the GPU Process images on the GPU Download image from GPU to CPU mem OpenCV CUDA example #include opencv2/opencv.hpp #include <
plify development of HPC applications, they can increase the difficulty of tuning GPU kernels (routines compiled for offloading to a GPU) for high performance by separating developers from many key details, such as what GPU code is generated and how it will be executed. To harness the full power of GPU-accelerated nodes, application
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GPU Tutorial 1: Introduction to GPU Computing Summary This tutorial introduces the concept of GPU computation. CUDA is employed as a framework for this, but the principles map to any vendor’s hardware. We provide an overview of GPU computation, its origins and development, before presenting both the CUDA hardware and software APIs. New Concepts
limitation, GPU implementers made the pixel processor in the GPU programmable (via small programs called shaders). Over time, to handle increasing shader complexity, the GPU processing elements were redesigned to support more generalized mathematical, logic and flow control operations. Enabling GPU Computing: Introduction to OpenCL
Possibly: OptiX speeds both ray tracing and GPU devel. Not Always: Out-of-Core Support with OptiX 2.5 GPU Ray Tracing Myths 1. The only technique possible on the GPU is “path tracing” 2. You can only use (expensive) Professional GPUs 3. A GPU farm is more expensive than a CPU farm 4. A
Latest developments in GPU acceleration for 3D Full Wave Electromagnetic simulation. Current and future GPU developments at CST; detailed simulation results. Keywords: gpu acceleration; 3d full wave electromagnetic simulation, cst studio suite, mpi-gpu, gpu technology confere
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