GPU-Based Visualization for Flight Simulation

GPU-Based Visualization for Flight Simulation Tim Woodard Director of Research and Development Diamond Visionics www.dvcsim.com GPU Technology Conference 2014 Flight Simulation Takes Off Flight Simulation Takes Off  Link’s Blue Box, 1943 Flight Simulation Takes Off  Link’s Blue Box, 1943  Terrain model-board and film, 50’s and 60’s Flight Simulation Takes Off  Link’s Blue Box, 1943  Terrain model-board and film, 50’s and 60’s  “Image Generators”, 70’s to present “Big Iron”       McDonnell Douglas VITAL Evans and Sutherland ESIG GE Compu-scene Link DIG SGI Onyx Improved rapidly “Big Iron”       McDonnell Douglas VITAL Evans and Sutherland ESIG GE Compu-scene Link DIG SGI Onyx Improved rapidly, but costly… Rise of the PC      McDonnell Douglas (VITAL) Evans and Sutherland (ESIG) GE (Compu-scene) Link (DIG) Improved rapidly, but VERY costly… 1999, NVIDIA GeForce 256 Rise (and fall?) of the PC  Moving to the PC-based GPU brought huge cost savings Rise (and fall?) of the PC  Moving to the PC-based GPU brought huge cost savings  But meant giving up a lot of capability and control      Real-time determinism Anti-aliasing Gen-lock Unified memory Computational power Flight Simulation vs. Gaming  Instructor-controlled conditions (time, weather, etc.)  Subjective tuning  Fidelity No aliasing No Z-fighting No LOD popping  Performance Never drop frames  20+ channels  Data… Flight Simulation vs. Gaming  Large gaming areas – “database” (E.g. continental, even planetary)  Legacy database standards (Government-defined)  Typical gaming approaches do not scale to massive datasets... (nor do traditional simulation approaches) Throw Hardware At It!  Moore’s Law continues…  …Via parallelism, not speed (for nearly 10 years now)  First with CPU, now with GPU Not So Fast  Free lunch is over…  Software must be architected for parallelism: Amdahl’s Law 𝑆= 1 𝑃 (1 − 𝑃) + 𝑛 S = speed up P = % of parallelization n = number of threads The Long Pole Prepare Source Data Compile Database Re-work Intermediate Database (LODs) Load/Render Database Compute ALL the LODs!  Pre-compute LODs for all possible paths into “polygon soup”  Very little of the result is typically used Compute ALL the LODs!  Pre-compute LODs for all possible paths into “polygon soup”  Very little of the result is typically used  Uses tremendous computing resources  Uses tremendous amount of storage space Stuck in Time  Static databases do not adapt to new data or GPU technology Stuck in Time  Static databases do not adapt to new data or GPU technology Stuck in Time  Static databases do not adapt to new data or GPU technology Underutilizes GPU Leveraging the GPU  Large/fast memory buffers  Programmability…  Vertex, fragment, geometry  Compute Run-time Scene Generation Prepare Source Data Source Data User-Defined Processing Rules/ Shaders Load/Render Source Data on GPU Deferred Commitment Case Study: Hardware Consolidation  One 4K projector from one GPU  Multiple GPUs per system Case Study: Lights  ~50 tunable parameters  100’s of thousands of lights possible at 60Hz Case Study: Grass  10’s of thousands of grass blades  Matches imagery color  Local wind model (helo rotor wash) Summary  Visualization in flight simulation continues to evolve rapidly.  GPU advancements have fundamentally changed how we do things and what is possible:  Improved fidelity  Improved performance  Deferred commitment, instant feedback Questions? Tim Woodard timw@dvcsim.com @TimAtDVC #GTC14 Thank you!

GPU-Based Visualization for Flight Simulation

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