DICE's APU13 Presentation slide deck bullet points.
1. MANTLE FOR DEVELOPERS JOHAN ANDERSSON – TECHNICAL DIRECTOR FROSTBITE ELECTRONIC ARTS
2. Mantle? Simplify advanced development  Improve performance  Enable developers to innovate  Challenge the status quo
3. Developer impact areas Control CPU performance Programmability GPU performance Platforms
4. Control New model Traditional Model: Black Box Explicit Model: Mantle  Middle-ground abstraction – compromise between performance & “usability”  Thin low-level abstraction to expose how hardware works  Hidden resource memory & state  App explicit memory management  Resource CPU access tied to device context  Resources are globally accessible  Driver analyzes & synchronizes implicitly  App explicit resource state transitions
5. Control App responsibility  Tell when render target will be used as a texture ‒ And many more resource state transitions  Don’t destroy resources that GPU is using ‒ Keep track with fences or frames  Manual dynamic resource renaming ‒ No DISCARD for driver resource renaming  Resource memory tiling  Powerful validation layer will help!
6. Control Explicit control enables  App high-level decisions & optimizations ‒ Has full scene information ‒ Easier to optimize performance & memory  Flexible & efficient memory management ‒ Linear frame allocators ‒ Memory pools ‒ Pinned memory  Reduced development time ‒ For advanced game engines & apps ‒ Easier to get to target performance & robustness
7. Control Explicit control enables  Transient resources ‒ Alias render targets within frame ‒ Major memory savings ‒ No need to pre-allocate everything  Light-weight driver ‒ Easier to develop & maintain ‒ Reduced CPU draw call overhead
8. CPU performance
9. CPU perf Core concepts  Descriptor sets  Monolithic pipelines  Command buffers
10. CPU perf Descriptor sets  Table with resource references to bind to graphics or compute pipeline Image Memory Sampler Link  Replaces traditional resource stage binding ‒ Major performance & flexibility advantage ‒ Closer to how the hardware works  Example 1: Single simple dynamic descriptor set ‒ Bind everything you need for a single draw call ‒ Close to DX/GL model but share between stages Dynamic descriptor set VertexBuffer (VS) Texture0 (VS+PS) Constants (VS) Texture1 (PS)  App managed - lots of strategies possible! ‒ Tiny vs huge sets ‒ Single vs multiple ‒ Static vs semi-static vs dynamic Texture2 (PS) Sampler0 (VS+PS)
11. CPU perf Descriptor sets  Table with resource references to bind to graphics or compute pipeline Image  Example 2: Reuse static set with nesting ‒ Reduce update time & memory usage Memory Static descriptor set Sampler Link Dynamic descriptor set  Replaces traditional resource stage binding ‒ Major performance & flexibility advantage ‒ Closer to how the hardware works Constants (VS) Link VertexBuffer (VS) Texture0 (VS+PS) Texture1 (PS) Texture2 (PS) Texture3 (PS)  App managed - lots of strategies possible! ‒ Tiny vs huge sets ‒ Single vs multiple ‒ Static vs semi-static vs dynamic Texture4 (PS) Sampler0 (VS+PS) Sampler1 (PS)
12. CPU perf Monolithic pipelines  Shader stages & select graphics state combined into single object ‒ No runtime compilation or patching needed! ‒ Significantly less runtime overhead to use Pipeline state  Supports parallel building & caching ‒ Fast loading times  Usage & management up to the app ‒ Static vs dynamic creation ‒ Amount of pipelines ‒ State usage IA DB VS HS DS Tessellator GS RS PS CB
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3. CPU perf Command buffers  Issue pipelined graphics & compute commands into a command buffer ‒ Bind graphics state, descriptor sets, pipeline ‒ Draw calls ‒ Render targets ‒ Clears ‒ Memory transfers ‒ NOT: resource mapping  Fully independent objects ‒ Create multiple every frame ‒ Or pre-build up front and reuse
14. CPU perf DX/GL parallelism CPU 0 CPU 1 CPU 2 Game Game Game Render Render Driver Render  Automatically extracts parallelism out of most apps   Doesn’t scale beyond 2-3 cores   Additional latency   Driver thread often bottleneck – can collide app threads  Render
15. CPU perf Parallel dispatch with Mantle CPU 0 Game Game Game CPU 1 Render Render Render CPU 2 Render Render Render CPU 3 Render Render Render CPU 4 Render Render Render  App can go fully wide with its rendering – minimal latency   Close to linear scaling with CPU cores   No driver threads – no overhead – no contention   Frostbite’s approach on all consoles – and on PC with Mantle! 
16. GPU performance
17. GPU perf GPU optimizations  Thanks to improved CPU performance – CPU will rarely be a bottleneck for the GPU ‒ CPU could help GPU more: ‒ Less brute force rendering ‒ Improve culling  Resource states ‒ Gives driver a lot more knowledge & flexibility ‒ Apps can avoid expensive/redundant transitions, such as surface decompression  Expose existing GPU functionality  Shader pipeline object – driver optimizations ‒ Can optimize with pipeline state knowledge ‒ Can optimize across all shader stages ‒ Quad & Rect-lists ‒ HW-specific MSAA & depth data access ‒ Programmable sample patterns ‒ And more..
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8. GPU perf Queues  Modern GPUs are heterogeneous machines with multiple engines Graphics ‒ Graphics pipeline ‒ Compute pipeline(s) ‒ DMA transfer ‒ Video encode/decode ‒ More…  Mantle exposes queues for the engines + synchronization primitives Compute DMA ... Queues GPU
19. GPU perf Queues Graphics Compute DMA ... Queues GPU
20. GPU perf Queue use cases  Async DMA transfers ‒ Copy resources in parallel with graphics or compute Copy DMA Graphics Render Other render Use copy
21. GPU perf Queue use cases  Async DMA transfers ‒ Copy resources in parallel with graphics or compute  Async compute together with graphics ‒ ALU heavy compute work at the same time as memory/ROP bound work to utilize idle units Compute Graphics GBuffer Non-shadowed lighting Shadowmap 0 Shadowmap 1 Final lighting
22. GPU perf Queue use cases  Async DMA transfers  Multiple compute kernels collaborating ‒ Copy resources in parallel with graphics or compute ‒ Can be faster than über-kernel ‒ Example: Compute geometry backend & compute rasterizer  Async compute together with graphics ‒ ALU heavy compute work at the same time as memory/ROP bound work to utilize idle units Compute 0 Compute 1 Graphics Compute Geometry Compute Rasterizer Ordinary Rendering
23. GPU perf Queue use cases  Async DMA transfers  Multiple compute kernels collaborating ‒ Copy resources in parallel with graphics or compute ‒ Can be faster than über-kernel ‒ Example: Compute geometry backend & compute rasterizer  Async compute together with graphics ‒ ALU heavy compute work at the same time as memory/ROP bound work to utilize idle units Compute Graphics Process0 Process1 Draw0  Compute as frontend for graphics pipeline ‒ Compute runs asynchronously ahead and prepares& optimizes geometry for graphics pipeline Process0 Draw1 Draw2
24. GPU perf Queue use cases  Async DMA transfers  Multiple compute kernels collaborating ‒ Copy resources in parallel with graphics or compute ‒ Can be faster than über-kernel ‒ Example: Compute geometry backend & compute rasterizer  Async compute together with graphics ‒ ALU heavy compute work at the same time as memory/ROP bound work to utilize idle units  Compute as frontend for graphics pipeline ‒ Compute runs asynchronously ahead and prepares& optimizes geometry for graphics pipeline  Game engines will build large GPU job graphs ‒ Move away from single sequential submission ‒ Just as we already have done on CPU
25. Programmability
26. Programmability Explicit Multi-GPU  Explicit control of GPU queues and synchronization, finally! ‒ Implement your own Alternate-Frame-Rendering ‒ Or something more exotic..  Use case: Workstation rendering with 4-8 GPUs ‒ Super high-quality rendering & simulation ‒ Load balance graphics & compute job graphs across GPUs ‒ 20-40 TFlops in a single machine!  Use case: Low-latency rendering ‒ Important for VR and competitive games ‒ Latency optimized GPU job graph scheduling ‒ VR: Simultaneously drive 2 GPUs (1 per eye)
27. Programmability New mechanisms  Command buffer predication & flow control ‒ GPU affecting/skipping submitted commands ‒ Go beyond DrawIndirect / DispatchIndirect ‒ Advanced variable workloads ‒ Advanced culling optimizations  Write occlusion query results into GPU buffer ‒ No CPU roundtrip needed ‒ Can drive predicated rendering ‒ Or use results directly in shaders (lens flares)
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8. Programmability Bindless resources  Mantle supports bindless resources ‒ Shaders can select resources to use instead of static binding from CPU ‒ Extension of the descriptor set support  Examples ‒ Performance optimizations – less data to update ‒ Logic & data structures that live fully on the GPU ‒ Scene culling & rendering ‒ Material representations  Key component that will open up a lot of opportunities! ‒ Deferred shading ‒ Raytracing
29. Platforms
30. Platforms Today  Mantle gives us strong benefits on Windows today ‒ Console-like performance & programmability on both Windows 7 and Windows 8 ‒ For us, well worth the dev time!  DX & GL are the industry standards ‒ Needed for platforms that do not support Mantle ‒ Needed by devs who do not want/need more control ‒ Have to have fallback paths for GL/DX, but not limit oneself to it  Mantle and PlayStation 4 will drive our future Frostbite designs & optimizations ‒ PS4 graphics API has great programmability & performance as well ‒ Share concepts, methods & optimization strategies
31. Platforms Linux & Mac  Want to see Mantle on Linux and Mac! ‒ Would enable support for our full engine & rendering ‒ Significantly easier to do efficient renderer with Mantle than with OpenGL  Use cases: ‒ Workstations ‒ R&D ‒ Not limited by WDDM ‒ Games ‒ Mantle + SteamOS = powerful combination!
32. Platforms Mobile  Mobile architectures are getting closer in capabilities to desktop GPUs  Want graphics API that allows apps to fully utilize the hardware ‒ Power efficient ‒ High performance ‒ Programmable  Major opportunity with Mantle – leap frog GL4, DX11 ‒ For mobile SoC vendors ‒ For Google and Apple
33. Platforms Multi-vendor?  Mantle is designed to be a thin hardware abstraction ‒ Not tied to AMD’s GCN architecture ‒ Forward compatible ‒ Extensions for architecture- and platform-specific functionality  Mantle would be a much more efficient graphics API for other vendors as well ‒ Most Mantle functionality can be supported on today’s modern GPUs  Want to see future version of Mantle supported on all platforms and on all modern GPUs! ‒ Become an active industry standard with IHVs and ISVs collaborating ‒ Enable us developers to innovate with great performance & programmability everywhere
34. Frostbite Battlefield 4  Mantle support is in development ‒ Core renderer (closer to PS4 than DX11) ‒ Implement all rendering techniques used in BF4 (many!) ‒ CPU optimizations (parallel dispatch, descriptor sets) ‒ GPU optimizations (minimize transitions, MSAA) ‒ R&D for advanced GPU optimizations ‒ Memory management ‒ Multi-GPU support ‒ ~2 months of work  Update targeting late December
35. Frostbite Plants vs Zombies: Garden Warfare  Very different rendering compared to BF4   Frostbite Mantle renderer will work out of the box  Focus on APU performance
36. Frostbite Future  All Frostbite games designed with Mantle ‒ 15 games in development across all of EA  Advanced Mantle rendering & use cases ‒ Lots of exciting R&D opportunities!  Want multi-vendor & multi-platform support!