SCIENTIFIC VISUALIZATION IN HPC

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1 April 4-7, 2016 Silicon Valley SCIENTIFIC VISUALIZATION IN HPC Peter Messmer, 4/4/2016

2 HIGH PERFORMANCE COMPUTING TODAY* "Yes," said Deep Thought, "I can do it." [Seven and a half million years later... ] The Answer to the Great Question... Of Life, the Universe and Everything... Is... Forty-two,' said Deep Thought, with infinite majesty and calm. Douglas Adams, Hitchhiker s Guide to the Galaxy *mostly 2

3 Latency Month Week HPC application Day Hour 5 min Accuracy Moves Flies 100 ms Has Engine Sit in it 30 ms 10 ms 3

4 Latency Month Week HPC application Day Hour 5 min Accuracy Moves Flies 100 ms Has Engine Sit in it Action Game 30 ms 10 ms 4

5 Latency Month Week HPC application Day CG Movie Hour 5 min Accuracy Moves Flies 100 ms Has Engine Sit in it Action Game 30 ms 10 ms Flight Simulator 5

6 Latency CG Movie Month Week Day Hour Parameter Space Exploration, Approximate models HPC application 5 min Accuracy Moves Flies 100 ms Has Engine Sit in it Action Game 30 ms 10 ms Flight Simulator 6

7 Latency CG Movie Month Week Day Hour Parameter Space Exploration, Approximate models HPC application 5 min Explorative Science, Real-time systems Accuracy Moves Flies 100 ms Has Engine Sit in it Action Game 30 ms 10 ms Opportunity! Flight Simulator 7

8 BONSAI WITH IN-SITU VIZ ON PIZ DAINT J. Bedorf, E. Gaburov, P.Messmer, S. Portegies Zwart Compute & Vis on 1024 GPU nodes Live Streaming Presented at at SC14, streaming from CSCS/Switzerland to to New Orleans 8

9 BONSAI WITH IN-SITU VIZ ON PIZ DAINT Compute & Vis on 1024 GPU nodes Live Streaming Presented at at SC14, streaming from CSCS/Switzerland to to New Orleans 9

10 10

11 VISUALIZATION RENDERING * * but it s a part of it Isosurfaces, Isovolumes Field Operators (Gradient, Curl,.. ) Streamlines Coordinate transformations Feature extraction Clip, Slice Compositing Surface Rendering Thresholding Binning, Resample Line Rendering Volume Rendering 11

12 VISUALIZATION PIPELINE Your typical scientific visualization system Simulation Analysis& Filtering Rendering Compositing Delivery Visualization - Analysis: Data processing to extract meaningful quantities of interest - Filtering: Conversion of simulation data into data ready for rendering - Rendering: Conversion of shapes to pixels (Fragment processing) - Compositing: Combination of independently generated pixels into final frame 12

13 VISUALIZATION TOOLKIT (VTK) Venerable backbone of scientific visualization Focus on visualization, not (only) rendering Provides more complex operations on data ( filtering ) Visualization pipeline At the core of many high-level viz tools Paraview, Visit,.. Developed by Kitware, open source Tue - 15:00 : S Visualization Toolkit: Improving Rendering and Compute on GPU's 13

14 VTK-M Visualization algorithms on modern architectures Ongoing development (Sandia, Kitware, ORNL,..) VTK type filters and more fine-grained worklets Platform portable (GPU, multicore CPU) Thrust, TBB backend Wed - 15:00 : S Adapting the Visualization Toolkit for Many-Core Processors with the VTK-m Library 14

15 TYPICAL HPC ENVIRONMENT Workstation on scientist s desk Remote HPC center Compute nodes not directly accessible Output from compute nodes: Workstation GPU Login Node - File transfer - X forwarding - Remote rendering Compute Node Compute Node GPU GPU 15

16 X-FORWARDING Be prepared for latencies ssh Y loginnode.edu ssh Y computenode No extra process on compute node Workstation GPU Login Node Rendering by workstation GPU X server on workstation needed Often prohibitively slow Compute Node Compute Node GPU GPU 16

17 REMOTE RENDERING Know your latencies Use compute node s GPU for rendering Capture renderings and ship pixel data to user Workstation GPU Login Node Compression is key Requires running X server on compute node* * Requirements will change with EGL Compute Node Compute Node GPU GPU 17

18 Remote visualization on Blue Waters Improvement in time to solution Limited resources in the local viz cluster Long data transfer times Stellar combustion visualized on Blue Waters (26 TB dataset) 6 GPUs in local viz cluster Data transfer Rendering 48 days 128 GPUs in HPC center 1 day 48x speed ups by using the Tesla GPUs in the HPC center Paul Woodward, U. Minnesota: HVR w/ OpenGL on Blue Waters Data courtesy of John Stone, UIUC 18 18

19 REMOTE RENDERING: VIDEO ENCODING Interactivity over large distances Open source approaches: TurboVNC + VirtualGL Currently not leveraging HW H264 encoder Commercial tools (e.g. Nice DCV) Leverages HW encoder No application modification needed NvENC library to access HW H264 encoder (lossless on Maxwell) Tue - 13:00: S VMD: Petascale Molecular Visualization and Analysis with Remote Video Streaming 19

20 OPENGL: GPU ACCELERATED RENDERING Primitives: points, lines, polygons Properties: colors, lighting, textures,.. View: camera position and perspective Shaders: Rendering to screen/framebuffer C-style functions, enums See e.g. What Every CUDA Programmer Should Know About OpenGL ( Mon - 10:00 : S High-Performance, Low-Overhead Rendering with OpenGL and Vulkan Mon - 14:00 : H Hangout: Maximizing Performance of CUDA and OpenGL Applications 20

21 VIS TOOLS EMBRACE OPENGL ON EGL Streamlined GPU accelerated off-screen rendering Prior to EGL: X server required for GPU accelerated OpenGL Full OpenGL on EGL announced at SC16 With EGL: OpenGL without X Major enabler for GPU rendering in HPC, incl. Cray systems* Quick adoption by vis tool developers * Driver version or newer required 21 4/20/2016

22 USE CASE: CSI ENSIGHT D EGL for batch renderer Customers post-process large collections of simulations offline Even though rendering takes place offscreen, EnSight requires that an X server is running, and is open enough to allow users to access it. At some sites, it is unacceptable to configure an X server to have wide open access. By using EGL to make our GL context and pbuffer, we can remove the need to start an Xserver, and solve all of these system management problems. Dave Bremer, CEI Image by Astec Inc 22 4/20/2016

23 PARAVIEW: DESIGNED FOR HPC Satisfying scientific computing needs Supports all major scientific data formats Extensive collection of operators : isosurface, streamlines, volume renderer, reductions, custom operators,.. Approachable user interface Supports remote, distributed memory vis Open source, free Extensible via plugins 23 4/20/2016

24 MODERN OPENGL FOR HPC VIZ Mandatory to access advanced rendering features VTK supports now OpenGL 3.2 Enables advanced shaders (AO, VXGI,..) Some algorithms well suited for distributed memory rendering GPU hardware support Data courtesy Florida Intl University & TACC 24

25 Bigger is better OPENGL RENDERING POWERHOUSE OpenGL vs OpenSWR 25

26 OPENGL NOT LIMITED TO RENDERING TASKS Interop goes both ways, esp with EGL CUDA->OpenGL typically one-way only EGL enables lighter weight access to OpenGL No X server needed Potential use of OpenGL for rasterization-like problems? Determine covered pixels 3D ordering/occlusion via Z-buffer 26

27 SCALABLE RENDERING AND COMPOSITING NVIDIA INDEX Large-scale (volume) data visualization Interactive visualization of TB of data Stand-alone or coupling into simulation HW Accelerated remote rendering Plugin for ParaView Mon - 10:00: S HPC Visualization Using NVIDIA IndeX 27

28 SCALABLE VOLUME RENDERING IN PARAVIEW Plugin enables GPU accelerated volume rendering Index plugin addresses shortcomings in ParaView built-in volume renderer Beta version supports - 3D structured, scalar grids - 32bit float, 16 bit/8bit uint - Overlay of opaque ParaView geometries (e.g. streamlines) Free plugin, requires commercial IndeX license RC coming out soon.. for enquiries Tue - 16:00 : S Toward Bridging the Gap Between High Quality and High Performance for HPC Visualization 28 4/20/2016

29 Advanced Rendering in scientific visualization Better insight with visual cues Two lights, no shadows Two lights, hard shadows, 1 shadow ray per light Ambient occlusion + two lights, 144 AO rays/hit Ray tracing offers ambient occlusion lighting, shadows, high quality transparent surfaces Courtesy of John Stone, UIUC 29

30 OPTIX RAY TRACING FRAMEWORK GPU accelerated ray-tracing framework Build your own RT application Generic Ray-Geometry interaction Rays with arbitrary payloads Multi-GPU-support Tue - 14:00 : H Hangout: CUDA for HPC Simulation and Visualization Tue - 14:00 : H Hangout: OptiX Ray Tracing Library: Best practices and Use-Case Consultation Wed -10:30 S: S Opticks: Optical Photon Simulation for High Energy Physics with NVIDIA OptiX 30

31 TELLING A BETTER STORY, VISUALLY Advanced rendering improves messaging Advanced rendering can help visual message, e.g. guiding the eye via depth of field Particularly useful for complex visualizations Interactive ray-tracing via NVIDIA Iray Post-processing of ParaView files Mon - 15:00 : H6142A - Hangout: Iray Rendering for Developers 31

32 PARALLEL COMPOSITING WITH ICE-T Modern networks remove compositing bottleneck Each node renders fraction of image Sort last compositing Widely used (Paraview, VisIt.. ) Critical element for real-time viz Up to 30 fps for 4k frames on 1024 nodes Cray XC30, Piz CSCS Tue- 14:30 : S Image Compositing on GPU-Accelerated Supercomputers 32

33 HIGH FRAMERATE = MINIMAL IMPACT ON SIMULATION FPS matter, even in HPC Real-time visualization only one use case Batch processing will not go away Acceptable time budget for visualization/analysis Up to the I/O time, ~ 2 % More diagnostics in the same time E.g. ParaView Cinema 33

34 VISUALIZATION-ENABLED SUPERCOMPUTERS CSCS Piz Daint NCSA Blue Waters ORNL Titan Galaxy formation Molecular dynamics -visualization-nvidia-tesla-gpus/ Cosmology highlights/visualization/66-accelerated-cosmologydata-anal.html 34

35 COMPUTE+VIS SUPPORTS MULTIPLE WORKFLOWS LEGACY WORKFLOW PARTITIONED SYSTEM CO-PROCESSING Separate compute & vis system Communication via file system Different nodes for different roles Communication via highspeed network Compute and visualization on same GPU Communication via hostdevice transfers or memcpy 35

36 - Minimize IO traffic IN-SITU VIS: ADVANTAGES AND OPPORTUNITIES - Exploit data locality - Less pressure on file system Workstation - Less time wasted in I/O - Reduce latency to first result - Monitoring, early termination GPU-accelerated Supercomputer - Enable real-time/interactive visualization - Novel workflows, new applications Tue 9:00: S Navigating the In-Situ Visualization Landscape File System 36

37 COSMO WITH IN-SITU VISUALIZATION Live, Interactive Weather Simulation COSMO-1 model, operational weather model in Switzerland 6 nodes Cray CS-Storm system 8 K80 GPUs/node 96 GPU sockets total ~ 20s per 0.7s NVIDIA IndeX for visualizaiton Tue - 13:30: S Co-Designing GPU-Based Systems and Tools for Numerical Weather Predictions 37

38 IN-SITU VISUALIZATION ON TITAN First prototype of ParaView in-situ visualization capabilities in pyfr (CFD) simulations, predicting jet engine acoustics Both compute and visualization running on Titan GPUs and streaming to a remote location When running PyFR at scale, it generates very large data sets that need analyzing for acoustics. The traditional post hoc method is simply not fit for purpose in situ visualization and processing are critical. We see a potential for 50x speed ups with in situ, which significantly accelerates our scientific discovery - Dr. Peter Vincent Imperial College Thu-10:30 : S Petascale Computational Fluid Dynamics with Python on GPUs Tue-15:00 : S Visualization Toolkit: Improving Rendering and Compute on GPU's 38

39 VISUALIZATION IN HPC Leverage graphics capabilities on heterogeneous nodes GPUs offer features for visualization, rendering, remote viz Modern networks enable parallel compositing at massive scale Graphics capabilities may help for graphics-like algorithms Supported by popular visualization tools Fast rendering relevant even for batch processing In-situ visualization for monitoring, steering, and other novel workflows 39

40 April 4-7, 2016 Silicon Valley THANK YOU JOIN THE NVIDIA DEVELOPER PROGRAM AT developer.nvidia.com/join

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