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© The Khronos® Group Inc. 2021 - Page 1
This work is licensed under a Creative Commons Attribution 4.0 International License
SYCL 2020
Specification Release
Michael Wong
SYCL WG Chair
Codeplay Distinguished Engineer
ISOCPP Director & VP
ISO C++ Directions Group
michael@codeplay.com | wongmichael.com/about
© The Khronos® Group Inc. 2021 - Page 2
This work is licensed under a Creative Commons Attribution 4.0 International License
Open, royalty-free interoperability
standards to harness the power of
GPU, multiprocessor and XR hardware
3D graphics, augmented and virtual
reality, parallel programming,
inferencing and vision acceleration
Non-profit, member-driven standards
organization, open to any company
Well-defined multi-company
governance and IP Framework
Founded in 2000
>150 Members ~ 40% US, 30% Europe, 30% Asia
Khronos Connects Software to Silicon
© The Khronos® Group Inc. 2021 - Page 3
This work is licensed under a Creative Commons Attribution 4.0 International License
Khronos Active Initiatives
3D Graphics
Desktop, Mobile
and Web
3D Assets
Authoring
and Delivery
Portable XR
Augmented and
Virtual Reality
Parallel Computation
Vision, Inferencing,
Machine Learning
Safety Critical APIs
© The Khronos® Group Inc. 2021 - Page 4
This work is licensed under a Creative Commons Attribution 4.0 International License
Khronos Compute Acceleration Standards
GPU
GPU rendering +
compute
acceleration
Heterogeneous
compute
acceleration
Single source C++ programming
with compute acceleration
Graph-based vision and
inferencing acceleration
Lower-level APIs
Direct Hardware Control
Intermediate
Representation
(IR) supporting
parallel execution
and graphics
Higher-level Languages and APIs
Streamlined development and
performance portability
GPU
FPGA DSP
Custom Hardware
GPU
CPU
CPU
CPU
AI/Tensor HW
Increasing industry interest in
parallel compute acceleration to
combat the ‘End of Moore’s Law’
SYCL and SPIR were
originally OpenCL
sub projects
© The Khronos® Group Inc. 2021 - Page 5
This work is licensed under a Creative Commons Attribution 4.0 International License
SYCL 2020 Launch!
Open Standard for Single Source C++ Parallel Programming
SYCL 2020 is released after 3 years of intense work
Significant adoption in Embedded, Desktop and HPC markets
Improved programmability, smaller code size, faster performance
Based on C++17, backwards compatible with SYCL 1.2.1
Simplify porting of standard C++ applications to SYCL
Closer alignment and integration with ISO C++
Backend acceleration API independent
SYCL 2020 increases expressiveness and simplicity
for modern C++ heterogeneous programming
© The Khronos® Group Inc. 2021 - Page 6
This work is licensed under a Creative Commons Attribution 4.0 International License
SYCL 2020 Industry Momentum
https://www.alcf.anl.gov/support-center/aurora/sycl-and-dpc-aurora
https://www.embeddedcomputing.com/technology/open-source/risc-v-open-source-ip/nsitexe-kyoto-microcomputer-and-codeplay-software-are-bringing-open-standards-programming-to-risc-v-vector-processor-for-hpc-and-ai-systems
https://www.nextplatform.com/2021/02/03/can-sycl-slice-into-broader-supercomputing/
https://www.phoronix.com/scan.php?page=news_item&px=hipSYCL-New-Lite-Runtime
https://software.intel.com/content/www/us/en/develop/articles/interoperability-dpcpp-sycl-opencl.html
https://www.renesas.com/br/en/about/press-room/renesas-electronics-and-codeplay-collaborate-opencl-and-sycl-adas-solutions
https://www.nersc.gov/news-publications/nersc-news/nersc-center-news/2021/nersc-alcf-codeplay-partner-on-sycl-for-next-generation-supercomputers/
https://research-portal.uws.ac.uk/en/publications/trisycl-for-xilinx-fpga
https://www.imaginationtech.com/news/press-release/tensorflow-gets-native-support-for-powervr-gpus-via-optimised-open-source-sycl-libraries/
SYCL support growing from
Embedded Systems through
Desktops to Supercomputers
© The Khronos® Group Inc. 2021 - Page 7
This work is licensed under a Creative Commons Attribution 4.0 International License
SYCL 2020 Major Features
• Unified Shared Memory (USM)
• Code with pointers can work naturally without buffers or accessors
• Parallel Reductions
• Added built-in reduction operation to avoid boilerplate code and achieve maximum
performance on hardware with built-in reduction operation acceleration
• Work group and subgroup algorithms
• Efficient parallel operations between work items
• Class template argument deduction (CTAD) and template deduction guides
• Simplified class template instantiation
• Simplified use of Accessors with a built-in reduction operation
• Reduces boilerplate code and streamlines the use of C++ software design patterns
• Expanded interoperability
• Efficient acceleration by diverse backend acceleration APIs
• SYCL atomic operations are now more closely aligned to standard C++ atomics
• Enhances parallel programming freedom
© The Khronos® Group Inc. 2021 - Page 8
This work is licensed under a Creative Commons Attribution 4.0 International License
SYCL Single Source C++ Parallel Programming
GPU
FPGA DSP
Custom Hardware
GPU
CPU
CPU
CPU
Standard C++
Application
Code
C++
Libraries
ML
Frameworks
C++ Template
Libraries
C++ Template
Libraries
C++ Template
Libraries
SYCL
Compiler
CPU
Compiler
CPU
One-MKL
One-DNN
OneDPC
SYCL-BLAS
SYCL-Eigen
SYCL-DNN
SYCL Parallel STL
...
C++ templates and lambda
functions separate host &
accelerated device code
Accelerated code
passed into device
OpenCL compilers
Complex ML frameworks
can be directly compiled
and accelerated
SYCL is ideal for accelerating larger
C++-based engines and applications
with performance portability
C++ Kernel Fusion can
give better performance
on complex apps and libs
than hand-coding
AI/Tensor HW
GPU
FPGA DSP
Custom Hardware
GPU
CPU
CPU
CPU
AI/Tensor HW
Other
Backends
© The Khronos® Group Inc. 2021 - Page 9
This work is licensed under a Creative Commons Attribution 4.0 International License
Parallel Industry Initiatives
2011
OpenCL 1.2
OpenCL C Kernel
Language
OpenCL 2.1
SPIR-V in Core
2015
OpenCL 2.2
2017 2020 202X
SYCL 1.2
C++11 Single source
programming
SYCL 1.2.1
C++11 Single source
programming
SYCL 2020
C++17 Single source
programming
Many backend options
SYCL 202X
C++20 Single source
programming
Many backend options
C++11 C++14 C++17 C++20
OpenCL 3.0
C++23
© The Khronos® Group Inc. 2021 - Page 10
This work is licensed under a Creative Commons Attribution 4.0 International License
SYCL Implementations in Development
Multiple Backends in Development
SYCL beginning to be supported on multiple
low-level APIs in addition to OpenCL
e.g., ROCm and CUDA
For more information: http://sycl.tech
Source Code
DPC++
Uses LLVM/Clang
Part of oneAPI
ComputeCpp
Multiple
Backends
triSYCL
Open source
test bed
hipSYCL
CUDA and
HIP/ROCm
Any CPU
OpenCL +
SPIR-V
Any CPU
OpenCL +
SPIR(-V)
OpenCL+PTX
Intel CPUs
Intel GPUs
Intel FPGAs
Intel CPUs
Intel GPUs
Intel FPGAs
AMD GPUs
(depends on driver stack)
Arm Mali
IMG PowerVR
Renesas R-Car
NVIDIA GPUs
Experim
ental
OpenMP
OpenCL +
SPIR/LLVM
XILINX FPGAs
POCL
(open-source OpenCL
supporting CPUs and NVIDIA
GPUs and more)
Any CPU
Experimental
OpenMP
ROCm
CUDA
AMD GPUs
NVIDIA GPUs
Any CPU
CUDA+PTX
NVIDIA GPUs
SYCL enables Khronos to
influence ISO C++ to (eventually)
support heterogeneous compute
SYCL, OpenCL and SPIR-V, as open industry
standards, enable flexible integration and
deployment of multiple acceleration technologies
VEO
Intel CPUs
NEC VEs
neoSYCL
SX-AURORA
TSUBASA
© The Khronos® Group Inc. 2021 - Page 11
This work is licensed under a Creative Commons Attribution 4.0 International License
Sensor Data
Training Data
Trained
Networks
Neural Network
Training
C++ Application
Code
SYCL in Embedded Systems
Compilation Ingestion
FPGA
DSP
Dedicated
Hardware
GPU
Vision / Inferencing
Engine
Compiled
Code
Hardware Acceleration APIs
Diverse Embedded Hardware
Multi-core CPUs, GPUs
DSPs, FPGAs, Tensor Cores
* Vulkan only runs on GPUs
Applications link to compiled
inferencing code or call
vision/inferencing API
Networks trained on high-end
desktop and cloud systems
Open industry standards, enable
flexible integration and deployment
of multiple acceleration technologies
© The Khronos® Group Inc. 2021 - Page 12
This work is licensed under a Creative Commons Attribution 4.0 International License
Choose
Algorithm
for target
Simulation
HPC Languages
Solver Libraries, Parallel RT
C++ Application uses
SYCL, Kokkos, Raja
SYCL in HPC/Supercomputers
CUDA/pthreads/
OpenACC/OpenCL
OpenMP for C
and Fortran
Need Languages that allow
control of these Data Issues
Set Data affinity, Data Layout, Data
movement, Data Locality, highly
Parameterized Code and dynamically
compose the algorithms (C++ templates,
parallel STL, inlining and fusion,
abstractions)
Math, ML, Data Libraries;C++ Std, C, Python Libraries
Libraries augment compiler
optimizations for Performance
Portable programs
Use open standards to run
Performance Portable code on new
generation, or different vendor’s,
hardware with compiler optimization,
explicit parametrization and
dynamically composed algorithm
Data
Productivity Languages
Big Data Stack, Stats Lib, Databases
Learning
Productivity Languages
Deep Learning, Linear Alg, ML
Implement
and Test
Algorithm
Based on IWOCL/SYCLCon 2020 keynote Hal FInkel: https://www.iwocl.org/wp-
content/uploads/iwocl-syclcon-2020-finkel-keynote-slides.pdf
Today’s Supercomputing
Development Workflow
needs knowledge of
system architecture and
tools that control data
Optimize
Algorithm
2021 2020 2021 2021
Three Pillars of
Science Problem
© The Khronos® Group Inc. 2020 - Page 13
This work is licensed under a Creative Commons Attribution 4.0 International License
Enabling Industry Engagement
• SYCL working group values industry feedback
- https://community.khronos.org/c/sycl
- https://sycl.tech
• What features would you like in future SYCL versions?
SYCL
Working
Group
SYCL
Advisory
Panels
Khronos GitHub
Contribute to SYCL open source
specs, CTS, tools and ecosystem
Khronos SYCL Forums, Slack Channels,
Stackoverflow, reddit, and SYCL.tech
Khronos members
https://www.khronos.org/members/
https://www.khronos.org/registry/SYCL/
Invited Experts
https://www.khronos.org/advisors/
Public contributions to Specification,
Conformance Tests and software
https://github.com/KhronosGroup/SYCL-CTS
https://github.com/KhronosGroup/SYCL-Docs
https://github.com/KhronosGroup/SYCL-Shared
https://github.com/KhronosGroup/SYCL-Registry
https://github.com/KhronosGroup/SyclParallelSTL
Open to all!
https://community.khronos.org/www.khr.io/slack
https://app.slack.com/client/TDMDFS87M/CE9UX4CHG
https://community.khronos.org/c/sycl/
https://stackoverflow.com/questions/tagged/sycl
https://www.reddit.com/r/sycl
https://github.com/codeplaysoftware/syclacademy
https://sycl.tech/
© The Khronos® Group Inc. 2020 - Page 14
This work is licensed under a Creative Commons Attribution 4.0 International License
Thank You! Questions?
• Khronos SYCL is creating a cutting-edge royalty-free open standard
- For C++ Heterogeneous compute, vision, inferencing acceleration
- https://www.khronos.org/sycl
• Any entity/individual is welcome to join Khronos to influence SYCL’s evolution
- https://www.khronos.org/members
• Join IWOCL/SYCLcon Conference
- Wednesday Apr 27-29, 2021
• Michael Wong
- michael@codeplay.com | wongmichael.com/about
Gather industry
requirements for future
open standards
Draft Specifications
Confidential to Khronos
members
Publicly Release
Specifications and
Conformance Tests
Gain early insights
into industry trends
and directions
Influence the design and direction
of key open standards that will
drive your business
Accelerate your time-to-
market with early access to
specification drafts
Network with domain
experts from diverse
companies in your industry
State-of-the-art IP
Framework protects your
Intellectual Property
Enhance your company reputation
as an industry leader through
Khronos participation
Benefits of Khronos Membership
Khronos
Standardization
Process

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SYCL 2020 Specification

  • 1. © The Khronos® Group Inc. 2021 - Page 1 This work is licensed under a Creative Commons Attribution 4.0 International License SYCL 2020 Specification Release Michael Wong SYCL WG Chair Codeplay Distinguished Engineer ISOCPP Director & VP ISO C++ Directions Group michael@codeplay.com | wongmichael.com/about
  • 2. © The Khronos® Group Inc. 2021 - Page 2 This work is licensed under a Creative Commons Attribution 4.0 International License Open, royalty-free interoperability standards to harness the power of GPU, multiprocessor and XR hardware 3D graphics, augmented and virtual reality, parallel programming, inferencing and vision acceleration Non-profit, member-driven standards organization, open to any company Well-defined multi-company governance and IP Framework Founded in 2000 >150 Members ~ 40% US, 30% Europe, 30% Asia Khronos Connects Software to Silicon
  • 3. © The Khronos® Group Inc. 2021 - Page 3 This work is licensed under a Creative Commons Attribution 4.0 International License Khronos Active Initiatives 3D Graphics Desktop, Mobile and Web 3D Assets Authoring and Delivery Portable XR Augmented and Virtual Reality Parallel Computation Vision, Inferencing, Machine Learning Safety Critical APIs
  • 4. © The Khronos® Group Inc. 2021 - Page 4 This work is licensed under a Creative Commons Attribution 4.0 International License Khronos Compute Acceleration Standards GPU GPU rendering + compute acceleration Heterogeneous compute acceleration Single source C++ programming with compute acceleration Graph-based vision and inferencing acceleration Lower-level APIs Direct Hardware Control Intermediate Representation (IR) supporting parallel execution and graphics Higher-level Languages and APIs Streamlined development and performance portability GPU FPGA DSP Custom Hardware GPU CPU CPU CPU AI/Tensor HW Increasing industry interest in parallel compute acceleration to combat the ‘End of Moore’s Law’ SYCL and SPIR were originally OpenCL sub projects
  • 5. © The Khronos® Group Inc. 2021 - Page 5 This work is licensed under a Creative Commons Attribution 4.0 International License SYCL 2020 Launch! Open Standard for Single Source C++ Parallel Programming SYCL 2020 is released after 3 years of intense work Significant adoption in Embedded, Desktop and HPC markets Improved programmability, smaller code size, faster performance Based on C++17, backwards compatible with SYCL 1.2.1 Simplify porting of standard C++ applications to SYCL Closer alignment and integration with ISO C++ Backend acceleration API independent SYCL 2020 increases expressiveness and simplicity for modern C++ heterogeneous programming
  • 6. © The Khronos® Group Inc. 2021 - Page 6 This work is licensed under a Creative Commons Attribution 4.0 International License SYCL 2020 Industry Momentum https://www.alcf.anl.gov/support-center/aurora/sycl-and-dpc-aurora https://www.embeddedcomputing.com/technology/open-source/risc-v-open-source-ip/nsitexe-kyoto-microcomputer-and-codeplay-software-are-bringing-open-standards-programming-to-risc-v-vector-processor-for-hpc-and-ai-systems https://www.nextplatform.com/2021/02/03/can-sycl-slice-into-broader-supercomputing/ https://www.phoronix.com/scan.php?page=news_item&px=hipSYCL-New-Lite-Runtime https://software.intel.com/content/www/us/en/develop/articles/interoperability-dpcpp-sycl-opencl.html https://www.renesas.com/br/en/about/press-room/renesas-electronics-and-codeplay-collaborate-opencl-and-sycl-adas-solutions https://www.nersc.gov/news-publications/nersc-news/nersc-center-news/2021/nersc-alcf-codeplay-partner-on-sycl-for-next-generation-supercomputers/ https://research-portal.uws.ac.uk/en/publications/trisycl-for-xilinx-fpga https://www.imaginationtech.com/news/press-release/tensorflow-gets-native-support-for-powervr-gpus-via-optimised-open-source-sycl-libraries/ SYCL support growing from Embedded Systems through Desktops to Supercomputers
  • 7. © The Khronos® Group Inc. 2021 - Page 7 This work is licensed under a Creative Commons Attribution 4.0 International License SYCL 2020 Major Features • Unified Shared Memory (USM) • Code with pointers can work naturally without buffers or accessors • Parallel Reductions • Added built-in reduction operation to avoid boilerplate code and achieve maximum performance on hardware with built-in reduction operation acceleration • Work group and subgroup algorithms • Efficient parallel operations between work items • Class template argument deduction (CTAD) and template deduction guides • Simplified class template instantiation • Simplified use of Accessors with a built-in reduction operation • Reduces boilerplate code and streamlines the use of C++ software design patterns • Expanded interoperability • Efficient acceleration by diverse backend acceleration APIs • SYCL atomic operations are now more closely aligned to standard C++ atomics • Enhances parallel programming freedom
  • 8. © The Khronos® Group Inc. 2021 - Page 8 This work is licensed under a Creative Commons Attribution 4.0 International License SYCL Single Source C++ Parallel Programming GPU FPGA DSP Custom Hardware GPU CPU CPU CPU Standard C++ Application Code C++ Libraries ML Frameworks C++ Template Libraries C++ Template Libraries C++ Template Libraries SYCL Compiler CPU Compiler CPU One-MKL One-DNN OneDPC SYCL-BLAS SYCL-Eigen SYCL-DNN SYCL Parallel STL ... C++ templates and lambda functions separate host & accelerated device code Accelerated code passed into device OpenCL compilers Complex ML frameworks can be directly compiled and accelerated SYCL is ideal for accelerating larger C++-based engines and applications with performance portability C++ Kernel Fusion can give better performance on complex apps and libs than hand-coding AI/Tensor HW GPU FPGA DSP Custom Hardware GPU CPU CPU CPU AI/Tensor HW Other Backends
  • 9. © The Khronos® Group Inc. 2021 - Page 9 This work is licensed under a Creative Commons Attribution 4.0 International License Parallel Industry Initiatives 2011 OpenCL 1.2 OpenCL C Kernel Language OpenCL 2.1 SPIR-V in Core 2015 OpenCL 2.2 2017 2020 202X SYCL 1.2 C++11 Single source programming SYCL 1.2.1 C++11 Single source programming SYCL 2020 C++17 Single source programming Many backend options SYCL 202X C++20 Single source programming Many backend options C++11 C++14 C++17 C++20 OpenCL 3.0 C++23
  • 10. © The Khronos® Group Inc. 2021 - Page 10 This work is licensed under a Creative Commons Attribution 4.0 International License SYCL Implementations in Development Multiple Backends in Development SYCL beginning to be supported on multiple low-level APIs in addition to OpenCL e.g., ROCm and CUDA For more information: http://sycl.tech Source Code DPC++ Uses LLVM/Clang Part of oneAPI ComputeCpp Multiple Backends triSYCL Open source test bed hipSYCL CUDA and HIP/ROCm Any CPU OpenCL + SPIR-V Any CPU OpenCL + SPIR(-V) OpenCL+PTX Intel CPUs Intel GPUs Intel FPGAs Intel CPUs Intel GPUs Intel FPGAs AMD GPUs (depends on driver stack) Arm Mali IMG PowerVR Renesas R-Car NVIDIA GPUs Experim ental OpenMP OpenCL + SPIR/LLVM XILINX FPGAs POCL (open-source OpenCL supporting CPUs and NVIDIA GPUs and more) Any CPU Experimental OpenMP ROCm CUDA AMD GPUs NVIDIA GPUs Any CPU CUDA+PTX NVIDIA GPUs SYCL enables Khronos to influence ISO C++ to (eventually) support heterogeneous compute SYCL, OpenCL and SPIR-V, as open industry standards, enable flexible integration and deployment of multiple acceleration technologies VEO Intel CPUs NEC VEs neoSYCL SX-AURORA TSUBASA
  • 11. © The Khronos® Group Inc. 2021 - Page 11 This work is licensed under a Creative Commons Attribution 4.0 International License Sensor Data Training Data Trained Networks Neural Network Training C++ Application Code SYCL in Embedded Systems Compilation Ingestion FPGA DSP Dedicated Hardware GPU Vision / Inferencing Engine Compiled Code Hardware Acceleration APIs Diverse Embedded Hardware Multi-core CPUs, GPUs DSPs, FPGAs, Tensor Cores * Vulkan only runs on GPUs Applications link to compiled inferencing code or call vision/inferencing API Networks trained on high-end desktop and cloud systems Open industry standards, enable flexible integration and deployment of multiple acceleration technologies
  • 12. © The Khronos® Group Inc. 2021 - Page 12 This work is licensed under a Creative Commons Attribution 4.0 International License Choose Algorithm for target Simulation HPC Languages Solver Libraries, Parallel RT C++ Application uses SYCL, Kokkos, Raja SYCL in HPC/Supercomputers CUDA/pthreads/ OpenACC/OpenCL OpenMP for C and Fortran Need Languages that allow control of these Data Issues Set Data affinity, Data Layout, Data movement, Data Locality, highly Parameterized Code and dynamically compose the algorithms (C++ templates, parallel STL, inlining and fusion, abstractions) Math, ML, Data Libraries;C++ Std, C, Python Libraries Libraries augment compiler optimizations for Performance Portable programs Use open standards to run Performance Portable code on new generation, or different vendor’s, hardware with compiler optimization, explicit parametrization and dynamically composed algorithm Data Productivity Languages Big Data Stack, Stats Lib, Databases Learning Productivity Languages Deep Learning, Linear Alg, ML Implement and Test Algorithm Based on IWOCL/SYCLCon 2020 keynote Hal FInkel: https://www.iwocl.org/wp- content/uploads/iwocl-syclcon-2020-finkel-keynote-slides.pdf Today’s Supercomputing Development Workflow needs knowledge of system architecture and tools that control data Optimize Algorithm 2021 2020 2021 2021 Three Pillars of Science Problem
  • 13. © The Khronos® Group Inc. 2020 - Page 13 This work is licensed under a Creative Commons Attribution 4.0 International License Enabling Industry Engagement • SYCL working group values industry feedback - https://community.khronos.org/c/sycl - https://sycl.tech • What features would you like in future SYCL versions? SYCL Working Group SYCL Advisory Panels Khronos GitHub Contribute to SYCL open source specs, CTS, tools and ecosystem Khronos SYCL Forums, Slack Channels, Stackoverflow, reddit, and SYCL.tech Khronos members https://www.khronos.org/members/ https://www.khronos.org/registry/SYCL/ Invited Experts https://www.khronos.org/advisors/ Public contributions to Specification, Conformance Tests and software https://github.com/KhronosGroup/SYCL-CTS https://github.com/KhronosGroup/SYCL-Docs https://github.com/KhronosGroup/SYCL-Shared https://github.com/KhronosGroup/SYCL-Registry https://github.com/KhronosGroup/SyclParallelSTL Open to all! https://community.khronos.org/www.khr.io/slack https://app.slack.com/client/TDMDFS87M/CE9UX4CHG https://community.khronos.org/c/sycl/ https://stackoverflow.com/questions/tagged/sycl https://www.reddit.com/r/sycl https://github.com/codeplaysoftware/syclacademy https://sycl.tech/
  • 14. © The Khronos® Group Inc. 2020 - Page 14 This work is licensed under a Creative Commons Attribution 4.0 International License Thank You! Questions? • Khronos SYCL is creating a cutting-edge royalty-free open standard - For C++ Heterogeneous compute, vision, inferencing acceleration - https://www.khronos.org/sycl • Any entity/individual is welcome to join Khronos to influence SYCL’s evolution - https://www.khronos.org/members • Join IWOCL/SYCLcon Conference - Wednesday Apr 27-29, 2021 • Michael Wong - michael@codeplay.com | wongmichael.com/about Gather industry requirements for future open standards Draft Specifications Confidential to Khronos members Publicly Release Specifications and Conformance Tests Gain early insights into industry trends and directions Influence the design and direction of key open standards that will drive your business Accelerate your time-to- market with early access to specification drafts Network with domain experts from diverse companies in your industry State-of-the-art IP Framework protects your Intellectual Property Enhance your company reputation as an industry leader through Khronos participation Benefits of Khronos Membership Khronos Standardization Process