Presentation MM-4104, Smart Sharpen using OpenCL in Adobe Photoshop CC – Challenges and Achievements, by Joseph Hsieh at the AMD Developer Summit, November 11-13, 2013.

1. SMART SHARPEN USING OPENCL IN PHOTOSHOP CC
– CHALLENGES AND ACHIEVEMENTS
JOSEPH HSIEH
ADOBE SYSTEMS INC.

2. TOPICS
 Table
‒ What is OpenCL?
‒ Why Adobe Photoshop CC chooses OpenCL?
‒ Smart Sharpen in Adobe Photoshop CC
‒ Challenges
‒ What have we learned?
‒ Demo
‒ Summary
‒ Q&A
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3. What is OpenCL

4. WHAT IS OPENCL?
 OpenCL is an open standard framework (supported by AMD, Apple, Intel, Nvidia, etc.) that allows
developer to write programs that execute on different hardware platforms – GPUs, CPUs, DSPs, etc.
 CUDA, GLSL, C++ AMP are competing GPGPU (General-Purpose Computing on Graphics Processing Units)
technologies.
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5. Why OpenCL

6. WHY ADOBE PHOTOSHOP CC CHOOSES OPENCL
 Some advanced algorithms are just not fast enough.
 GPU computing is suitable for algorithms that benefits from massive parallelization.
 Cross-Platform (OpenCL and OpenGL Shading language (GLSL) are the only two cross-platform GPGPU
solution).
 Easier to map algorithm into OpenCL code than GLSL.
 Highly efficient (capable of using fast cache memory).
 Learning curves – Syntax (C99 plus vector support operations).
 OpenCL is available on many latest mobile devices.
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7. Smart Sharpen in
Adobe Photoshop CC

8. SHARPENING
 From Scott Kelby, “I haven’t met a digital camera (or scanned) photo that I didn’t think needed a little
sharpening”.
 For very blurred image, you need to do deblur, not the sharpening.
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9. RENOVATED ADOBE PHOTOSHOP CC SMART SHARPEN FEATURE
 Adobe renovated the legacy smart sharpen to
‒ Addresses “noise get boosted when you sharpen” issue.
‒ Better overall quality (preserve color).
‒ Reduce the halo effect.
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10. COMPARISON BETWEEN LEGACY AND CURRENT SMART SHARPEN
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11. COMPARISON BETWEEN LEGACY (ACCURATE) AND CURRENT VERSION
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12. COMPARISON BETWEEN UNSHARP MASK AND SMART SHARPEN
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13. COMPARISON BETWEEN UNSHARP MASK THRESHOLD AND SMART SHARPEN
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14. SHARPENING TIPS
 Sharpen the image on a separate layer.
 Blending Mode: luminosity
 Adjust opaque percentage
 You may want to denoise before sharpening.
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15. PERFORMANCE CONCERN
 User experience – responsiveness is important.
‒ CPU Optimization.
‒ Multi-threading
‒ Vectorization using intrinsic instructions
 Still not fast enough…
‒ Is the algorithm parallelizable?
‒ Is GPGPU Optimization suitable for our sharpening algorithm?
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16. CHALLENGES IN SMART SHARPEN OPENCL DEVELOPMENT
 Need to rethink about the algorithm.
 Limited resources. (global memory, local memory, and private memory)
 Algorithm is memory bound.
 Avoid memory corruption.
 Debug strategy.
 How to make solid OpenCL kernels?
 Optimization strategy.
 Driver Issues? (better re-check the OpenCL spec and your kernel first…).
 Quality control (GPU on different vendor platforms).
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17. WHAT WE HAVE LEARNED
 Reference code first (making sure you know the algorithm right).
 Divide and conquer (easy to verify).
 Always design for easy to do unit testing.
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18. WHAT WE HAVE LEARNED
 Optimization strategies (general practices):
‒ Always profile first.
‒ Algorithm parallelization.
‒ Global memory read as less as possible. (???)
‒ Memory access pattern.
‒ Avoid branching.
‒ Avoid edge condition handling.
‒ Arithmetic complexity (% is bad).
‒ Avoid bank conflict as much as possible. (???)
‒ Maximize the lazy synchronization.
‒ Trade-offs.
‒ Do not make the conclusion before doing the experiments…
‒ Optimization for certain vendor devices?
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19. WHAT WE HAVE LEARNED
 Quality control across various GPUs.
‒ Design of testing scenarios.
‒ Automation
‒ Collaborate with vendors.
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20. SMART SHARPEN BENCHMARK ON 5616X3744 (21 MEGA) PIXELS IMAGE
In seconds
45
40
35
30
25
Radius 64
20
Radius 4
Radius 1
15
10
5
0
AMD Radeon 7970
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i7-3770K 3.5GHz

21. AMD CodeXL

22. AMD CODEXL – TOOL FOR HETEROGENEOUS COMPUTING
 Features:
‒ OpenCL debug
‒ GPU profiling
‒ Analyze OpenCL kernel
‒ Collect OpenCL application trace
‒ Integrated with Microsoft Visual Studio
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23. BENEFIT OF USING AMD CODEXL
 Helps you to optimize your OpenCL kernel efficiently.
‒ Analyze the usage of VGPR, SGPR, Local Memory, etc.
‒ Profiling.
‒ Host code efficiency.
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24. AMD CODEXL- OPENCL KERNEL DEBUG
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25. AMD CODEXL- MEMORY OBJECT VIEWER
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26. AMD CODEXL – TIMELINE VISUALIZATION
 Visualize host code execution, data transfer, and kernel execution.
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27. AMD CODEXL – PERFORMANCE COUNTER
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28. AMD CODEXL – KERNEL OCCUPANCY VIEWER
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29. OpenCL 2.0

30. OPENCL 2.0 NEW FEATURES
 Shared virtual memory
‒ Great for APUs and integrated GPUs.
 Image2D, Image3D memory object read_write modifier.
 Dynamic Parallelism: kernel can enqueue other kernels.
‒ Avoid to transfer execution and data between the device and host.
 Pipe
‒ FIFO memory object.
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31. Smart Sharpen Demo

32. Summary

33. SUMMARY
 Adobe Photoshop CC adopts OpenCL to accelerate great features.
 Adobe dedicates to deliver the best user experience.
‒ Embrace advanced solid technologies.
‒ Works closely with vendors to insure fully tested high quality software.
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34. Q&A

35. Thank You

36. DISCLAIMER & ATTRIBUTION
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