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GPGPU algorithms in games

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GPGPU algorithms in games

  1. 1. GPGPU ALGORITHMS IN GAMESHow Heterogeneous Systems Architecture can beleveraged to optimize algorithms in video gamesMatthijs De SmedtNixxes Software B.V.Lead Graphics Programmer
  2. 2. CONTENTS A short introduction Current usage of GPGPU in games Heterogeneous Systems Architecture Examples made possible by HSA | HSA Algorithms in Games | June 13th, 2012
  4. 4. VIDEOGAMES Games are near real-time simulations CPU Response time is key Input Most systems run in sync with the output frequency – Rendering 60 frames per second – Allows for 16ms of processing time Simulate Framerate is limited either by: – GPU Render – CPU – Display (VSync) GPU Render | HSA Algorithms in Games | June 13th, 2012
  5. 5. HARDWARE Typical hardware target for PC games: – One multicore CPU – One GPU Multiple GPUs: CrossFire – Transparent to the application – Driver alternates frames between GPUs GPUs are becoming more general purpose: – General Purpose GPU algorithms (GPGPU) CrossFire | HSA Algorithms in Games | June 13th, 2012
  7. 7. INTRODUCTION TO GPGPU Rendering is a sequence of parallel algorithms GPUs are great at parallel computation Evolution of hardware and software to general purpose First GPGPU was accomplished with programmable rendering – DirectX – OpenGL Second generation using dedicated GPGPU APIs: – CUDA – OpenCL – DirectCompute Third generation of GPGPU on the way: – Heterogeneous Systems Architecture | HSA Algorithms in Games | June 13th, 2012
  8. 8. GPGPU IN GAMES Some GPGPU algorithms are being used in games right now. For example: – Physics  Particles  Fluid simulation  Destruction – Specialized graphics algorithms  Post-processing All these algorithms drive visual effects GPU particle system by Fairlight | HSA Algorithms in Games | June 13th, 2012
  9. 9. CURRENT PHYSICS EXAMPLE GPGPU particle simulation using DirectCompute CPU Great for simulating thousands of visible particles Results of simulation are never copied back to CPU Call GPU – Can not interfere with gameplay – Not synced in networked games Example: Smoke particles that affect game AI GPU Simulate particles Render particles | HSA Algorithms in Games | June 13th, 2012
  10. 10. GPGPU LIMITATIONS Why isn’t GPGPU used more for non-graphics? Latency – DirectX has many layers and buffers – DirectX commands are buffered up to multiple frames – Actual execution on the GPU is delayed Copy overhead – GPU cannot directly access application memory – Must copy all data from and to the application Functionality – Constrained programming models | HSA Algorithms in Games | June 13th, 2012
  12. 12. HETEROGENEOUS SYSTEMS ARCHITECTURE New hardware and softwareHardware Software New features on discrete GPUs  "Drivers" Accelerated Processing Unit – HSA provides a new, thin Compute API – Next generation processor – Very low latency – Multiple CPU and GPU cores on – Unified Address Space the same die – Exposes more hardware capabilities – Shared memory access  HSA Intermediate Language – Soon to be as widespread as – Virtual ISA multicore CPUs – Introduces CPU programming features to the GPU | HSA Algorithms in Games | June 13th, 2012
  13. 13. USING THE APU Distinction between two hardware configurations APU without discrete GPU – Found in many laptops, soon in many desktops – Use the on-die GPU for rendering APU with discrete GPU: – Hard-core gamers will still use discrete GPUs – Asymmetrical CrossFire – Or: Dedicate the on-die GPU to Compute algorithms  Could result in massive speedup of algorithms  Using SIMD co-processors to offload the CPU is familiar to PS3 developers | HSA Algorithms in Games | June 13th, 2012
  14. 14. COPY OVERHEAD Current Compute APIs require the application to explicitly copy all input and output memory – Copying can easily takes longer than processing on CPU! – Only small datasets or very expensive computations benefit from GPGPU HSA introduces a Unified Address Space for CPU and GPU memory – CPU pointers on the GPU – Virtual memory on the GPU  Paging over PCI-Express (discrete) or shared memory controller (APU) – Fully coherent – Will make GPGPU an option for many more algorithms | HSA Algorithms in Games | June 13th, 2012
  15. 15. LATENCY DirectX commands are buffered When the GPU is fully loaded this buffer is saturated Delay between scheduling and executing a GPGPU program on a busy GPU can take multiple frames – Results will be several frames behind – Game simulation needs all objects to be in sync GPGPU is currently impractical to use for anything but visual effects | HSA Algorithms in Games | June 13th, 2012
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  20. 20. LATENCY HSA’s new Compute API will reduce latency How to deal with a saturated GPU? A second GPU – Dedicate the APU to Compute – Virtually no latency HSA feature: Graphics pre-emption – Context switching on the GPU  Interrupt a graphics task (typically a large command list)  Execute Compute algorithm  Switch back to graphics – Can be used both on discrete GPUs or on the APU Choose the solution best suited to your needs | HSA Algorithms in Games | June 13th, 2012
  21. 21. APU USAGE EXAMPLE Schedule ExecuteDirectCompute GPU CPU HSA Frame Execute | HSA Algorithms in Games | June 13th, 2012
  22. 22. PROGRAMMING MODEL HSA Intermediate Language: HSAIL Designed for parallel algorithms JIT compiles your algorithm to CPU or GPU hardware – Also makes multi-core SIMD programming easy! High level language features – Object-oriented programming – Virtual functions – Exceptions Debugging SysCall support – I/O | HSA Algorithms in Games | June 13th, 2012
  24. 24. PHYSICS Current GPGPU physics solutions only output to the renderer With HSA you can simulate physics on the GPU and get the results back in the same frame Use hardware acceleration to compute physics for gameplay objects Reduced CPU load More objects, higher fidelity | HSA Algorithms in Games | June 13th, 2012
  25. 25. FRUSTUM CULLING Videogames tend to be GPU-bound Avoid rendering what cannot be seen Cull objects outside the camera viewport – Test the bounding box of every object against the camera frustum – Currently done on the CPU – Lots of vector math – Can be computed completely in parallel! CPU needs the results immediately – HSA will allow low-latency execution | HSA Algorithms in Games | June 13th, 2012
  26. 26. OCCLUSION CULLING Objects may be hidden behind others: Occlusion Final per-pixel occlusion is only known after rendering the scene Approximate occlusion by rendering low-detail geometry – This kind of occlusion culling is currently being done on CPU or on SPUs – Rendering is better suited to GPUs HSA solution: – Software rasterization in Compute on the GPU – HSA does not yet expose graphics pipeline  Software occlusion culling in Battlefield 3 – Still much faster than a multicore CPU | HSA Algorithms in Games | June 13th, 2012
  27. 27. SORTING Typically several long lists per frame need sorting Sorting on the GPU using a parallel sort algorithm – Ken Batcher: Bitonic or Odd-even mergesort Copy overhead currently negates the performance advantage of using a GPU sorting algorithm HSA solution: – Unified Address Space – GPU can sort in-place in system memory | HSA Algorithms in Games | June 13th, 2012
  28. 28. ASSET DECOMPRESSION Game assets are stored compressed on disk Decompression is expensive The usage of some compression algorithms is prevented by CPU speed Games are moving away from loading screens An APU with Unified Address Space – Can be used to decompress new assets without taxing the CPU or discrete GPU – Perhaps even use HSAIL I/O to read from disk – A better streaming experience for gamers | HSA Algorithms in Games | June 13th, 2012
  29. 29. PATHFINDING Some strategy games simulate thousands of units Pathfinding over complex terrain with thousands of moving units is very expensive Clever approximate solutions are often used – Supreme Commander 2 “Flow field” GPGPU pathfinding with HSA – Use one GPU thread per unit to do a deep search for an optimal path – With HSA such an algorithm can page all requisite data from system memory and write back found paths – APU could be fully saturated with pathfinding without impacting framerate | HSA Algorithms in Games | June 13th, 2012
  30. 30. CONCLUSION Many algorithms in games are suitable for offloading to the GPU Heterogeneous Systems Architecture solves two major obstacles – Latency – Memory access HSAIL allows for entirely new kinds of GPGPU programs APUs can be used to offload the CPU HSA will finally make GPUs available to developers as full-featured co-processors | HSA Algorithms in Games | June 13th, 2012
  31. 31. THANK YOU Any questions? | HSA Algorithms in Games | June 13th, 2012
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