Optimizing the Graphics Pipeline with Compute, GDC 2016
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The document presents optimizations for the graphics pipeline, particularly focusing on compute-centric techniques aimed at improving GPU performance while handling numerous draw calls. It discusses the challenges posed by tiny draw calls and the necessity for efficient culling methods that minimize wasted computation. Furthermore, the document elaborates on various culling strategies, batching techniques, and data management approaches essential for optimizing rendering in graphics applications.
![Acronyms
Optimizations and algorithms presented are AMD GCN-centric [1][8]
VGT Vertex Grouper Tessellator
PA Primitive Assembly
CP Command Processor
IA Input Assembly
SE Shader Engine
CU Compute Unit
LDS Local Data Share
HTILE Hi-Z Depth Compression
GCN Graphics Core Next
SGPR Scalar General-Purpose Register
VGPR Vector General-Purpose Register
ALU Arithmetic Logic Unit
SPI Shader Processor Interpolator](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-2-320.jpg)
![Motivation – Opportunity
Coarse cull on CPU, refine on GPU
Latency between CPU and GPU prevents optimizations
GPGPU Submission!
Depth-aware culling
Tighten shadow bounds sample distribution shadow maps [21]
Cull shadow casters without contribution [4]
Cull hidden objects from color pass
VR late-latch culling
CPU submits conservative frustum and GPU refines
Triangle and cluster culling
Covered by this presentation](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-15-320.jpg)
![Motivation – Opportunity
Maps directly to graphics pipeline
Offload tessellation hull shader work
Offload entire tessellation pipeline! [16][17]
Procedural vertex animation (wind, cloth, etc.)
Reusing results between multiple passes & frames
Maps indirectly to graphics pipeline
Bounding volume generation
Pre-skinning
Blend shapes
Generating GPU work from the GPU [4] [13]
Scene and visibility determination
Treat your draws as data!
Pre-build
Cache and reuse
Generate on GPU](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-16-320.jpg)
![Cluster Culling
Generate triangle clusters using spatially coherent bucketing in spherical coordinates
Optimize each triangle cluster to be cache coherent
Generate optimal bounding cone of each cluster [19]
Project normals on to the unit sphere
Calculate minimum enclosing circle
Diameter is the cone angle
Center is projected back to Cartesian for cone normal
Store cone in 8:8:8:8 SNORM
Cull if dot(cone.Normal, -view) < -sin(cone.angle)](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-28-320.jpg)
![Cluster Culling
Coarse reject clusters of triangles [4]
Cull against:
View (Bounding Cone)
Frustum (Bounding Sphere)
Hi-Z Depth (Screen Space Bounding Box)
Be careful of perspective distortion! [22]
Spheres become ellipsoids under projection](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-30-320.jpg)
![Compaction
V_MBCNT_LO_U32_B32 [5]
Masked bit count of the lower 32 threads (0-31)
V_MBCNT_HI_U32_B32 [5]
Masked bit count of the upper 32 threads (32-63)
For each thread, returns the # of active threads which come before it.](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-38-320.jpg)
![Per-Triangle Culling
Each thread in a wavefront processes 1 triangle
Cull masks are balloted and counted to determine compaction index
Maintain vertex reuse across a wavefront
Maintain vertex reuse across all wavefronts - ds_ordered_count [5][15]
+0.1ms for ~3906 work items – use wavefront limits](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-42-320.jpg)
![Depth Tile Culling (NDC)
Another available culling approach is to do manual depth testing
Perform an LDS optimized parallel reduction [9], storing out the conservative depth
value for each tile
16x16 Tiles](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-65-320.jpg)
![Depth Pyramid Culling (NDC)
Another approach to depth culling is a hierarchical Z pyramid [10][11][23]
Populate the Hi-Z pyramid after depth laydown
Construct a mip-mapped screen resolution texture
Culling can be done by comparing the depth of a bounding volume with the depth stored in the Hi-Z
pyramid
int mipMapLevel = min(ceil(log2(max(longestEdge, 1.0f))), levels - 1);](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-67-320.jpg)
![AMD GCN HTILE
Depth acceleration meta data called HTILE [6][7]
Every group of 8x8 pixels has a 32bit meta data block
Can be decoded manually in a shader and used for 1 test -> 64 pixel rejection
Avoids slow hardware decompression or resummarize
Avoids losing Hi-Z on later depth enabled render passes
DEPTH HTILE](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-68-320.jpg)
![AMD GCN HTILE
DS_SWIZZLE_B32 [5]
V_READLANE_B32 [5]](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-70-320.jpg)
![Software Z
One problem with using depth for culling is availability
Many engines do not have a full Z pre-pass
Restricts asynchronous compute scheduling
Wait for Z buffer laydown
You can load the Hi-Z pyramid with software Z!
In Frostbite since Battlefield 3 [12]
Done on the CPU for the upcoming GPU frame
No latency
You can prime HTILE!
Full Z pre-pass
Minimal cost](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-72-320.jpg)
![Hardware Tessellation
Mesh Data
Compute Shader
Structured Work Queue #1
(Patches with factor [1…1]
Tessellation Factors
Structured Work Queue #2
(Patches with factor [2…7]
Tessellation Factors
Structured Work Queue #3
(Patches with factor [8…N]
Tessellation Factors
Patches with factor 0 (culled) are not
processed further, and do not get
inserted to any work queue.](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-92-320.jpg)
![Hardware Tessellation
Structured Work Queue #1
(Patches with factor [1…1]
Tessellation Factors
Structured Work Queue #2
(Patches with factor [2…7]
Tessellation Factors
Structured Work Queue #3
(Patches with factor [8…N]
Tessellation Factors
Compute Shader
Patch SubD 1 -> 4
Tessellation Factor 1/4
Tessellated Draw
Non-Tessellated Draw
Low Expansion Factor
GCN Friendly
High Expansion Factor
GCN Unfriendly
No Expansion Factor
Avoid Tessellator!](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-93-320.jpg)
![Summary
Small and inefficient draws are a problem
Compute and graphics are friends
Use all the available GPU resources
Asynchronous compute is extremely powerful
Lots of cool GCN instructions available
Check out AMD GPUOpen GeometryFX [20]](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-94-320.jpg)
![References
[1] “The AMD GCN Architecture – A Crash Course” – Layla Mah
[2] “Clipping Using Homogenous Coordinates” – Jim Blinn, Martin Newell
[3] "Triangle Scan Conversion using 2D Homogeneous Coordinates“ - Marc Olano, Trey Greer
[4] “GPU-Driven Rendering Pipelines” – Ulrich Haar, Sebastian Aaltonen
[5] “Southern Islands Series Instruction Set Architecture” – AMD
[6] “Radeon Southern Islands Acceleration” – AMD
[7] “Radeon Evergreen / Northern Islands Acceleration” - AMD
[8] “GCN Architecture Whitepaper” - AMD
[9] “Optimizing Parallel Reduction In CUDA” – Mark Harris
[10] “Hierarchical-Z Map Based Occlusion Culling” – Daniel Rákos
[11] “Hierarchical Z-Buffer Occlusion Culling” – Nick Darnell
[12] “Culling the Battlefield: Data Oriented Design in Practice” – Daniel Collin
[13] “The Rendering Pipeline – Challenges & Next Steps” – Johan Andersson
[14] “GCN Performance Tweets” – AMD
[15] “Learning from Failure: … Abandoned Renderers For Dreams PS4 …” – Alex Evans
[16] “Patch Based Occlusion Culling For Hardware Tessellation” - Matthias Nießner, Charles Loop
[17] “Tessellation In Call Of Duty: Ghosts” – Wade Brainerd
[18] “MiniEngine Framework” – Alex Nankervis, James Stanard
[19] “Optimal Bounding Cones of Vectors in Three Dimensions” – Gill Barequet, Gershon Elber
[20] “GPUOpen GeometryFX” – AMD
[21] “Sample Distribution Shadow Maps” – Andrew Lauritzen
[22] “2D Polyhedral Bounds of a Clipped, Perspective-Projected 3D Sphere” – Mara and McGuire
[23] “Practical, Dynamic Visibility for Games” - Stephen Hill](https://image.slidesharecdn.com/gdc2016compute-160318234955/85/Optimizing-the-Graphics-Pipeline-with-Compute-GDC-2016-97-320.jpg)
Optimizing the Graphics Pipeline with Compute, GDC 2016
- 1. Optimizing the Graphics Pipeline with Compute Graham Wihlidal Sr. Rendering Engineer, Frostbite
- 2. Acronyms Optimizations and algorithms presented are AMD GCN-centric [1][8] VGT Vertex Grouper Tessellator PA Primitive Assembly CP Command Processor IA Input Assembly SE Shader Engine CU Compute Unit LDS Local Data Share HTILE Hi-Z Depth Compression GCN Graphics Core Next SGPR Scalar General-Purpose Register VGPR Vector General-Purpose Register ALU Arithmetic Logic Unit SPI Shader Processor Interpolator
- 4. libEdge
- 6. / clock / clock / clock
- 7. 12 CU * 64 ALU * 2 FLOPs 1,536 ALU ops / cy 18 CU * 64 ALU * 2 FLOPs 2,304 ALU ops / cy 64 CU * 64 ALU * 2 FLOPs 8,192 ALU ops / cy
- 8. 1,536 ALU ops / 2 engines 768 ALU ops per triangle 2,304 ALU ops / 2 engines 1,017 ALU ops per triangle 8,192 ALU ops / 4 engines 2,048 ALU ops per triangle
- 9. 768 ALU ops / 2 ALU per cy = 384 instruction limit 1,017 ALU ops / 2 ALU per cy = 508 instruction limit 2,048 ALU ops / 2 ALU per cy = 1024 instruction limit
- 10. Can anyone here cull a triangle in less than 384 instructions on Xbox One? … I sure hope so ☺
- 11. Motivation – Death By 1000 Draws DirectX 12 promised millions of draws! Great CPU performance advancements Low overhead Power in the hands of (experienced) developers Console hardware is a fixed target GPU still chokes on tiny draws Common to see 2nd half of base pass barely utilizing the GPU Lots of tiny details or distant objects – most are Hi-Z culled Still have to run mostly empty vertex wavefronts More draws not necessarily a good thing
- 12. Motivation – Death By 1000 Draws
- 13. Motivation – Primitive Rate Wildly optimistic to assume we get close to 2 prims per cy – Getting 0.9 prim / cy If you are doing anything useful, you will be bound elsewhere in the pipeline You need good balance and lucky scheduling between the VGTs and PAs Depth of FIFO between VGT and PA Need positions of a VS back in < 4096 cy, or reduces primitive rate Some games hit close to peak perf (95+% range) in shadow passes Usually slower regions in there due to large triangles Coarse raster only does 1 super-tile per clock Triangles with bounding rectangle larger than 32x32? Multi-cycle on coarse raster, reduces primitive rate
- 14. Motivation – Primitive Rate Benchmarks that get 2 prims / cy (around 1.97) have these characteristics: VS reads nothing VS writes only SV_Position VS always outputs 0.0f for position - Trivially cull all primitives Index buffer is all 0s - Every vertex is a cache hit Every instance is a multiple of 64 vertices – Less likely to have unfilled VS waves No PS bound – No parameter cache usage Requires that nothing after VS causes a stall Parameter size <= 4 * PosSize Pixels drain faster than they are generated No scissoring occurs PA can receive work faster than VS can possibly generate it Often see tessellation achieve peak VS primitive throughout; one SE at a time
- 15. Motivation – Opportunity Coarse cull on CPU, refine on GPU Latency between CPU and GPU prevents optimizations GPGPU Submission! Depth-aware culling Tighten shadow bounds sample distribution shadow maps [21] Cull shadow casters without contribution [4] Cull hidden objects from color pass VR late-latch culling CPU submits conservative frustum and GPU refines Triangle and cluster culling Covered by this presentation
- 16. Motivation – Opportunity Maps directly to graphics pipeline Offload tessellation hull shader work Offload entire tessellation pipeline! [16][17] Procedural vertex animation (wind, cloth, etc.) Reusing results between multiple passes & frames Maps indirectly to graphics pipeline Bounding volume generation Pre-skinning Blend shapes Generating GPU work from the GPU [4] [13] Scene and visibility determination Treat your draws as data! Pre-build Cache and reuse Generate on GPU
- 17. Culling Overview
- 18. Culling Overview Scene Consists of: Collection of meshes Specific view Camera, light, etc.
- 19. Culling Overview Batch Configurable subset of meshes in a scene Meshes within a batch share the same shader and strides (vertex/index) Near 1:1 with DirectX 12 PSO (Pipeline State Object)
- 20. Culling Overview Mesh Section Represents an indexed draw call (triangle list) Has its own: Vertex buffer(s) Index buffer Primitive count Etc.
- 21. Culling Overview Work Item Optimal number of triangles for processing in a wavefront AMD GCN has 64 threads per wavefront Each culling thread processes 1 triangle Work item processes 256 triangles
- 22. Culling Overview Batch Work Item Mesh Section Batch Mesh Section Mesh SectionMesh Section Work Item Work Item Work Item Work Item Work Item Work Item Work Item Multi Draw Indirect Draw Args Draw Args Draw Args Draw Args Culling Culling Culling Culling Culling Culling Culling Culling Draw Call Compaction (No Zero Size Draws) Draw Args Draw Args Draw Args Scene …
- 23. Mapping Mesh ID to MultiDraw ID Indirect draws no longer know the mesh section or instance they came from Important for loading various constants, etc. A DirectX 12 trick is to create a custom command signature Allows for parsing a custom indirect arguments buffer format We can store the mesh section id along with each draw argument block PC drivers use compute shader patching Xbox One has custom command processor microcode support OpenGL has gl_DrawId which can be used for this SPI Loads StartInstanceLocation into reserved SGPR and adds to SV_InstanceID A fallback approach can be an instancing buffer with a step rate of 1 which maps from instance id to draw id
- 24. Mapping Mesh ID to MultiDraw ID Mesh Section Id Draw Args Index Count Per Instance Instance Count Start Index Location Base Vertex Location Start Instance Location
- 25. De-Interleaved Vertex Buffers P0 P1 P2 P3 … N0 N1 N2 N3 … TC0 TC1 TC2 TC3 … Draw Call P0 N0 TC0 P1 N1 TC1 P2 N2 TC2 … Draw Call Do This! De-Interleaved vertex buffers are optimal on GCN architectures They also make compute processing easier!
- 26. De-Interleaved Vertex Buffers Helpful for minimizing state changes for compute processing Constant vertex position stride Cleaner separation of volatile vs. non-volatile data Lower memory usage overall More optimal for regular GPU rendering Evict cache lines as quickly as possible!
- 27. Cluster Culling
- 28. Cluster Culling Generate triangle clusters using spatially coherent bucketing in spherical coordinates Optimize each triangle cluster to be cache coherent Generate optimal bounding cone of each cluster [19] Project normals on to the unit sphere Calculate minimum enclosing circle Diameter is the cone angle Center is projected back to Cartesian for cone normal Store cone in 8:8:8:8 SNORM Cull if dot(cone.Normal, -view) < -sin(cone.angle)
- 29. Cluster Culling 64 is convenient on consoles Opens up intrinsic optimizations Not optimal, as the CP bottlenecks on too many draws Not LDS bound 256 seems to be the sweet spot More vertex reuse Fewer atomic operations Larger than 256? 2x VGTs alternate back and forth (256 triangles) Vertex re-use does not survive the flip
- 30. Cluster Culling Coarse reject clusters of triangles [4] Cull against: View (Bounding Cone) Frustum (Bounding Sphere) Hi-Z Depth (Screen Space Bounding Box) Be careful of perspective distortion! [22] Spheres become ellipsoids under projection
- 31. Draw Compaction
- 32. Compaction At 133us - Efficiency drops as we hit a string of empty draws At 151us - 10us of idle time
- 33. Compaction Count = Min(MaxCommandCount, pCountBuffer)
- 34. Compaction Parallel Reduction Keep > 0 Count Args We can do better!
- 35. Compaction Parallel prefix sum to the rescue! 0 0 0 1 2 3 3 4 4 5 5 6 7 8 8 9
- 36. Compaction __XB_Ballot64 Produce a 64 bit mask Each bit is an evaluated predicate per wavefront thread 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 __XB_Ballot64(threadId & 1)
- 37. Compaction 1 0 0 1 1 1 0 1 0 1 0 1 1 1 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 __XB_Ballot64(indexCount > 0) & = Thread 5 Execution Mask Thread 5 Population Count “popcnt” = 3
- 38. Compaction V_MBCNT_LO_U32_B32 [5] Masked bit count of the lower 32 threads (0-31) V_MBCNT_HI_U32_B32 [5] Masked bit count of the upper 32 threads (32-63) For each thread, returns the # of active threads which come before it.
- 39. Compaction 1 0 0 1 1 1 0 1 0 1 0 1 1 1 0 1 0 0 0 1 2 3 3 4 4 5 5 6 7 8 8 9 __XB_MBCNT64(__XB_Ballot64(indexCount > 0)) 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
- 40. Compaction No more barriers! Atomic to sync multiple wavefronts Read lane to replicate global slot to all threads
- 41. Triangle Culling
- 42. Per-Triangle Culling Each thread in a wavefront processes 1 triangle Cull masks are balloted and counted to determine compaction index Maintain vertex reuse across a wavefront Maintain vertex reuse across all wavefronts - ds_ordered_count [5][15] +0.1ms for ~3906 work items – use wavefront limits
- 43. Per-Triangle Culling For Each Triangle Unpack Index and Vertex Data (16 bit) Orientation and Zero Area Culling (2DH) Small Primitive Culling (NDC) Frustum Culling (NDC) Count Number of Surviving Indices Compact Index Stream (Preserving Ordering) Reserve Output Space for Surviving Indices Write out Surviving Indices (16 bit) Depth Culling – Hi-Z (NDC) Perspective Divide (xyz/w) Scalar Branch (!culled) Scalar Branch (!culled) Scalar Branch (!culled) __XB_GdsOrderedCount (Optional) __XB_MBCNT64 __XB_BALLOT64
- 44. Per-Triangle Culling Without ballot Compiler generates two tests for most if-statements 1) One or more threads enter the if-statement 2) Optimization where no threads enter the if-statement With ballot (or high level any/all/etc.), or if branch on scalar value (__XB_MakeUniform) Compiler only generates case# 2 Skips extra control flow logic to handle divergence Use ballot for force uniform branching and avoid divergence No harm letting all threads execute the full sequence of culling tests
- 46. Triangle Orientation and Zero Area (2DH)
- 51. Rasterizer Efficiency 16 pixels / clock 100% Efficiency 1 pixel / clock 6.25% Efficiency 12 pixels / clock 75% Efficiency
- 52. Vi Vj
- 53. Small Primitive Culling (NDC) This triangle is not culled because it encloses a pixel center any(round(min) == round(max))
- 54. Small Primitive Culling (NDC) This triangle is culled because it does not enclose a pixel center any(round(min) == round(max))
- 55. Small Primitive Culling (NDC) This triangle is culled because it does not enclose a pixel center any(round(min) == round(max))
- 56. Small Primitive Culling (NDC) This triangle is not culled because the bounding box min and max snap to different coordinates This triangle should be culled, but accounting for this case is not worth the cost any(round(min) == round(max))
- 60. Frustum Culling
- 61. Frustum Culling (NDC) 0,0 1,10,1 1,0 Max Min Max Min Min.Y > 1 Max.X < 0 Min.X > 1 Max.Y < 0
- 64. Depth Culling
- 65. Depth Tile Culling (NDC) Another available culling approach is to do manual depth testing Perform an LDS optimized parallel reduction [9], storing out the conservative depth value for each tile 16x16 Tiles
- 66. Depth Tile Culling (NDC) ~41us on XB1 @ 1080p Bypasses LDS storage Bandwidth bound Shared with our light tile culling
- 67. Depth Pyramid Culling (NDC) Another approach to depth culling is a hierarchical Z pyramid [10][11][23] Populate the Hi-Z pyramid after depth laydown Construct a mip-mapped screen resolution texture Culling can be done by comparing the depth of a bounding volume with the depth stored in the Hi-Z pyramid int mipMapLevel = min(ceil(log2(max(longestEdge, 1.0f))), levels - 1);
- 68. AMD GCN HTILE Depth acceleration meta data called HTILE [6][7] Every group of 8x8 pixels has a 32bit meta data block Can be decoded manually in a shader and used for 1 test -> 64 pixel rejection Avoids slow hardware decompression or resummarize Avoids losing Hi-Z on later depth enabled render passes DEPTH HTILE
- 69. AMD GCN HTILE
- 70. AMD GCN HTILE DS_SWIZZLE_B32 [5] V_READLANE_B32 [5]
- 71. AMD GCN HTILE Manually encode; skip the resummarize on half resolution depth! HTILE encodes both near and far depth for each 8x8 pixel tile. Stencil Enabled = 14 bit near value, and a 6 bit delta towards far plane Stencil Disabled = MinMax depth encoded in 2x 14 bit UNORM pairs
- 72. Software Z One problem with using depth for culling is availability Many engines do not have a full Z pre-pass Restricts asynchronous compute scheduling Wait for Z buffer laydown You can load the Hi-Z pyramid with software Z! In Frostbite since Battlefield 3 [12] Done on the CPU for the upcoming GPU frame No latency You can prime HTILE! Full Z pre-pass Minimal cost
- 77. Batching Fixed memory budget of N buffers * 128k triangles 128k triangles = 384k indices = 768 KB 3 MB of memory usage, for up to 524288 surviving triangles in flight 128k triangles (768KB) 128k triangles (768KB) 128k triangles (768KB) 128k triangles (768KB) Render 128k triangles (768KB) 128k triangles (768KB) 128k triangles (768KB) 128k triangles (768KB) Render
- 78. Batching Mesh Section (20k tri) Mesh Section (34k tri) Mesh Section (4k tri) Mesh Section (20k tri) Mesh Section (70k tri) Culling (434k triangles) … 434k / 512k capacity Output #0 Output #1 Output #2 Output #0 Output #1 Output #2 Render #1 Render #0 Output #3 Output #3
- 79. Culling (546k triangles) Batching Mesh Section (20k tri) Mesh Section (34k tri) Mesh Section (4k tri) Mesh Section (20k tri) Mesh Section (70k tri) … 546k / 512k capacity Output #0 Output #1 Output #2 Render #0,0 Output #0 Output #1 Output #2 Render #1 Output #0 Render #0,1 Output #3 Output #3
- 80. Batching Dispatch #0 Render #0 Dispatch #1 Dispatch #2 Dispatch #3 Render #1 Render #2 Render #3Startup Cost Overlapping culling and render on the graphics pipe is great But there is a high startup cost for dispatch #0 (no graphics to overlap) If only there were something we could use….
- 81. Batching Asynchronous compute to the rescue! We can launch the dispatch work alongside other GPU work in the frame Water simulation, physics, cloth, virtual texturing, etc. This can slow down “Other GPU Stuff” a bit, but overall frame is faster! Just be careful about what you schedule culling with We use wait on lightweight label operations to ensure that dispatch and render are pipelined correctly Dispatch #0 Render #0 Dispatch #1 Dispatch #2 Dispatch #3 Render #1 Render #2 Render #3Other GPU Stuff
- 82. Performance 443,429 triangles @ 1080p 171 unique PSOs
- 83. Performance Filter Exclusively Culled Inclusively Culled Orientation 46% 204,006 46% 204,006 Depth* 42% 187,537 20% 90,251 Small* 30% 128,705 8% 37,606 Frustum* 8% 35,182 4% 16,162 * Scene Dependent Processed 100% 443,429 Culled 78% 348,025 Rendered 22% 95,404
- 84. Performance Cull Draw Total 0.26ms 4.56ms 4.56ms 0.15ms 3.80ms 3.80ms 0.06ms 0.47ms 0.47ms No Tessellation Platform XB1 (DRAM) PS4 (GDDR5) PC (Fury X) Base 5.47ms 4.56ms 0.79ms Cull Draw Total 0.24ms 4.54ms 4.78ms 0.13ms 3.76ms 3.89ms 0.06ms 0.47ms 0.53ms Synchronous Asynchronous 443,429 triangles @ 1080p 171 unique PSOs No Cluster Culling
- 85. Performance Cull Draw Total 0.26ms 11.2ms 11.2ms 0.15ms 8.10ms 8.10ms 0.06ms 0.64ms 0.64ms Tessellation Factor 1-7 (Adaptive Phong) Platform XB1 (DRAM) PS4 (GDDR5) PC (Fury X) Base 19.3ms 12.8ms 3.01ms Cull Draw Total 0.24ms 11.1ms 11.3ms 0.13ms 8.08ms 8.21ms 0.06ms 0.64ms 0.70ms AsynchronousSynchronous 443,429 triangles @ 1080p 171 unique PSOs No Cluster Culling
- 86. Future Work Reuse results between multiple passes Once for all shadow cascades Depth, gbuffer, emissive, forward, reflection Cube maps – load once, cull each side Xbox One supports switching PSOs with ExecuteIndirect Single submitted batch! Further reduce bottlenecks Move more and more CPU rendering logic to GPU Improve asynchronous scheduling
- 87. Future Work Instancing optimizations Each instance (re)loads vertex data Synchronous dispatch Near 100% L2$ hit ALU bound on render - 24 VGPRs, measured occupancy of 8 1.5 bytes bandwidth usage per triangle Asynchronous dispatch Low L2$ residency - other render work between culling and render VMEM bound on render 20 bytes bandwidth usage per triangle
- 88. Future Work Maximize bandwidth and throughput Load data into LDS chunks, bandwidth amplification Partition data into per-chunk index buffers Evaluate all instances More tuning of wavefront limits and CU masking
- 90. Hardware Tessellation Input Assembler Vertex (Local) Shader Hull Shader Tessellator Domain (Vertex) Shader Rasterizer Pixel Shader Output Merger • Tessellation Factors • Silhouette Orientation • Back Face Culling • Frustum Culling • Coarse Culling (Hi-Z)
- 91. Hardware Tessellation Input Assembler Vertex (Local) Shader Hull (Pass-through) Shader Tessellator Domain (Vertex) Shader Rasterizer Pixel Shader Output Merger Load Final Factors Mesh Data • Tessellation Factors • Silhouette Orientation • Back Face Culling • Frustum Culling • Coarse Culling (Hi-Z) Compute Shader
- 92. Hardware Tessellation Mesh Data Compute Shader Structured Work Queue #1 (Patches with factor [1…1] Tessellation Factors Structured Work Queue #2 (Patches with factor [2…7] Tessellation Factors Structured Work Queue #3 (Patches with factor [8…N] Tessellation Factors Patches with factor 0 (culled) are not processed further, and do not get inserted to any work queue.
- 93. Hardware Tessellation Structured Work Queue #1 (Patches with factor [1…1] Tessellation Factors Structured Work Queue #2 (Patches with factor [2…7] Tessellation Factors Structured Work Queue #3 (Patches with factor [8…N] Tessellation Factors Compute Shader Patch SubD 1 -> 4 Tessellation Factor 1/4 Tessellated Draw Non-Tessellated Draw Low Expansion Factor GCN Friendly High Expansion Factor GCN Unfriendly No Expansion Factor Avoid Tessellator!
- 94. Summary Small and inefficient draws are a problem Compute and graphics are friends Use all the available GPU resources Asynchronous compute is extremely powerful Lots of cool GCN instructions available Check out AMD GPUOpen GeometryFX [20]
- 96. Acknowledgements Matthäus Chajdas (@NIV_Anteru) Ivan Nevraev (@Nevraev) Alex Nankervis Sébastien Lagarde (@SebLagarde) Andrew Goossen James Stanard (@JamesStanard) Martin Fuller (@MartinJIFuller) David Cook Tobias “GPU Psychiatrist” Berghoff (@TobiasBerghoff) Christina Coffin (@ChristinaCoffin) Alex “I Hate Polygons” Evans (@mmalex) Rob Krajcarski Jaymin “SHUFB 4 LIFE” Kessler (@okonomiyonda) Tomasz Stachowiak (@h3r2tic) Andrew Lauritzen (@AndrewLauritzen) Nicolas Thibieroz (@NThibieroz) Johan Andersson (@repi) Alex Fry (@TheFryster) Jasper Bekkers (@JasperBekkers) Graham Sellers (@grahamsellers) Cort Stratton (@postgoodism) David Simpson Jason Scanlin Mike Arnold Mark Cerny (@cerny) Pete Lewis Keith Yerex Andrew Butcher (@andrewbutcher) Matt Peters Sebastian Aaltonen (@SebAaltonen) Anton Michels Louis Bavoil (@LouisBavoil) Yury Uralsky Sebastien Hillaire (@SebHillaire) Daniel Collin (@daniel_collin)
- 97. References [1] “The AMD GCN Architecture – A Crash Course” – Layla Mah [2] “Clipping Using Homogenous Coordinates” – Jim Blinn, Martin Newell [3] "Triangle Scan Conversion using 2D Homogeneous Coordinates“ - Marc Olano, Trey Greer [4] “GPU-Driven Rendering Pipelines” – Ulrich Haar, Sebastian Aaltonen [5] “Southern Islands Series Instruction Set Architecture” – AMD [6] “Radeon Southern Islands Acceleration” – AMD [7] “Radeon Evergreen / Northern Islands Acceleration” - AMD [8] “GCN Architecture Whitepaper” - AMD [9] “Optimizing Parallel Reduction In CUDA” – Mark Harris [10] “Hierarchical-Z Map Based Occlusion Culling” – Daniel Rákos [11] “Hierarchical Z-Buffer Occlusion Culling” – Nick Darnell [12] “Culling the Battlefield: Data Oriented Design in Practice” – Daniel Collin [13] “The Rendering Pipeline – Challenges & Next Steps” – Johan Andersson [14] “GCN Performance Tweets” – AMD [15] “Learning from Failure: … Abandoned Renderers For Dreams PS4 …” – Alex Evans [16] “Patch Based Occlusion Culling For Hardware Tessellation” - Matthias Nießner, Charles Loop [17] “Tessellation In Call Of Duty: Ghosts” – Wade Brainerd [18] “MiniEngine Framework” – Alex Nankervis, James Stanard [19] “Optimal Bounding Cones of Vectors in Three Dimensions” – Gill Barequet, Gershon Elber [20] “GPUOpen GeometryFX” – AMD [21] “Sample Distribution Shadow Maps” – Andrew Lauritzen [22] “2D Polyhedral Bounds of a Clipped, Perspective-Projected 3D Sphere” – Mara and McGuire [23] “Practical, Dynamic Visibility for Games” - Stephen Hill
- 98. Thank You! [email protected] Questions? Twitter - @gwihlidal “If you’ve been struggling with a tough ol’ programming problem all day, maybe go for a walk. Talk to a tree. Trust me, it helps.“ - Bob Ross, Game Dev
- 99. Instancing Optimizations Can do a fast bitonic sort of the instancing buffer for optimal front-to-back order Utilize DS_SWIZZLE_B32 Swizzles input thread data based on offset mask Data sharing within 32 consecutive threads Only 32 bit, so can efficiently sort 32 elements You could do clustered sorting Sort each cluster’s instances (within a thread) Sort the 32 clusters