OpenCL - The Open Standard for Parallel Programming of Heterogeneous Systems

OpenCL - The Open Standard for Parallel Programming of Heterogeneous Systems
OpenCL for Parallel Programming of Heterogeneous Systems
OpenCL™ (Open Computing Language) is an open, royalty-free standard for cross-platform, parallel programming of diverse accelerators found in supercomputers, cloud servers, personal computers, mobile devices and embedded platforms. OpenCL greatly improves the speed and responsiveness of a wide spectrum of applications in numerous market categories including professional creative tools, scientific and medical software, vision processing, and neural network training and inferencing.
Broad Adoption and Use
OpenCL 3.0
OpenCL 3.0 aligns the OpenCL roadmap to enable developer-requested
functionality to be broadly deployed by hardware vendors, and it significantly increases deployment
flexibility by empowering conformant OpenCL implementations to focus on functionality relevant to
their target markets.
An Introduction to OpenCL
OpenCL Image: FluidX3D CFD © Dr. Moritz Lehmann.
The Essential Resources for OpenCL Development
Specification & Key Resources
Thanks to the support of the Khronos membership and our passionate developer community, there is a
full set of well-supported developer information and educational resources available to help you get
you up and running with your OpenCL application development.
Specification
- in the OpenCL registry (HTML
and PDF).
Software Development Kit (SDK)
- all
the components needed to develop OpenCL applications (headers, bindings, loader, utility
libraries, samples and more).
OpenCL Guide
- an introductory read
that covers the background and key concepts of OpenCL.
OpenCL 3.0 Reference
Pages
- indexed reference to the API.
OpenCL 3.0
Quick Reference Card
- handy guide to the API functions and the OpenCL C language.
Clang Support
- Clang
can be used to compile OpenCL kernels for execution on a device.
OpenCL Intercept Layer
- intercept
and modify OpenCL calls for debugging and performance analysis.
SPIR-V
- OpenCL code can be compiled to run on any
device supporting the Khronos SPIR-V portable intermediate representation.
OpenCL Conformance Test Suite (CTS)
helps to create a reliable platform for developers.
OpenCL on GPUInfo.org
- reads and displays
OpenCL information and uploads to the database.
Featured Event
Blogs, Releases and More ...
Featured News and Blogs
View All OpenCL
News
Adding Unified Shared Virtual Memory (SVM) to OpenCL
The OpenCL working group has been working on a follow-on to OpenCL 2.0 SVM and we would love
your feedback.
OpenCL 3.0.19 Released
This maintenance update adds numerous bug fixes and clarifications and adds two new extensions: cl_khr_spirv_queries and cl_khr_external_memory_android_hardware
_buffer
Learn
more
New Open Source VirtIO-GPU OpenCL Driver
Discover how you can use the host GPU to accelerate operations in a virtual machine using a
VirtIO-based graphics adapter, and VCL, an OpenCL driver by Qualcomm.
Learn
more
Low-Level Parallel Programming
An Overview of OpenCL
OpenCL speeds applications by offloading their most computationally intensive code onto accelerator
processors - or devices. OpenCL developers use C or C++-based kernel languages to code programs that
are passed through a device compiler for parallel execution on accelerator devices.
Programming and Runtime Framework for Application Acceleration
Offload compute-intensive kernels onto parallel heterogeneous processors
CPUs, GPUs, DSPs, FPGAs, Tensors Processors, etc.
OpenCL or OpenCL for C++ language support
Other Khronos Compute Standards
OpenCL provides the industry with the lowest 'close-to-metal' processor-agile execution layer for
accelerating applications, libraries and engines, and also providing a code generation target for
compilers. Unlike 'GPU-only' APIs, such as Vulkan, OpenCL enables use of a diverse range of
accelerators including multi-core CPUs, GPUs, DSPs, FPGAs and dedicated hardware such as inferencing
engines.
OpenCL Deployment Flexibility
As the industry landscape of platforms and devices grows more complex, tools are evolving the enable
OpenCL applications to be deployed onto platforms that do not have available native OpenCL drivers.
For example, the open source
clspv compiler
and
clvk API translator
enable OpenCL applications to be run
over a Vulkan run-time. This gives OpenCL developers significant flexibility on where and how they
can deploy their OpenCL applications.
OpenCL Programming Model
An OpenCL application is split into host and device parts with host code written using a general
programming language such as C or C++ and compiled by a conventional compiler for execution on a
host CPU.
The device compilation phase can be done online, i.e. during execution of an application using
special API calls. It can alternatively be compiled before executing the application into the
machine binary or special portable intermediate representation defined by Khronos called
SPIR-V
. There are also domain specific languages and
frameworks that can compile to OpenCL either using source-to-source translations or generating
binary/SPIR-V, for example Halide.
The C++ for OpenCL Kernel Language
The OpenCL working group has transitioned from the original OpenCL C++ kernel language first defined
in OpenCL 2.0 to C++ for OpenCL developed by the open source community to provide improved features
and compatibility with OpenCL C. C++ for OpenCL is supported by
Clang
along with
documentation
. It enables
developers to use most C++17 features in OpenCL kernels. It is largely backwards compatible with
OpenCL C 2.0 enabling it to be used to program accelerators with OpenCL 2.0 or above with conformant
drivers that support SPIR-V. Its implementation in Clang can be tracked via the
OpenCL in Clang Support Page
A Consistent Platform for Developers
OpenCL Implementations
Widespread Adoption
OpenCL is widely adopted with the majority of vendors now offering conformant implementations of
OpenCL 3.0 and 2.0. Most of these offer public access to drivers and development platforms,
including:
AMD
- OpenCL runtimes for AMD GPUs
Arm
- OpenCL
for the Immortalis and Mali GPUs
Google - OpenCL for Google Pixel and Tensor platforms (not exposed as a public API)
Imagination
- Open source GPU driver deliverables
Intel
- OpenCL Runtimes for Intel Processors (CPU, GPU and FPGA)
Kalray
OpenCL for MPPA Coolidge processor
MediaTek
- OpenCL for
SoC platforms
NVIDIA
- OpenCL 3.0 conformant in R465 and
later drivers
POCL
- an open source implementation of the OpenCL
standard
Qualcomm
- OpenCL SDK and an OpenCL ML SDK
RustiCL
- an OpenCL implementation on top of
Gallium drivers
Samsung - Undisclosed product
TI
- OpenCL for a
range of TI processor/DSP platforms
VeriSilicon
- OpenCL on
Vivante GPU IP Series
Development Implementations
(non Conformant)
Mobileye
- an OpenCL implementation for EyeQ SoCs
About Conformance Testing
The OpenCL Conformance Test Suite (CTS) is
available on GitHub
and helps to create a
reliable platform for developers by ensuring that OpenCL is implemented consistently across all
platforms. If your company is developing a product that implements OpenCL, and passes CTS, then you
should consider becoming an official adopter to enjoy the following benefits -- and you don't need
to be a Khronos member to become an Adopter.
Usage of the OpenCL name and logo in association with your product
IP protection under the Khronos IP Framework
Products promoted in the Khronos OpenCL Conformant Products listing
Widely Adopted & Deployed
Industry Support for OpenCL
“OpenCL is the most pervasive, cross-vendor, open standard for low-level
heterogeneous parallel programming—widely used by applications, libraries,
engines, and compilers that need to reach the widest range of diverse
processors. OpenCL 2.X delivers significant functionality, but OpenCL 1.2 has
proven itself as the baseline needed by all vendors and markets. OpenCL 3.0
integrates tightly organized optionality into the monolithic 2.2 specification,
boosting deployment flexibility that will enable OpenCL to raise the bar on
pervasively available functionality in future core specifications.”
Neil Trevett
Vice President at NVIDIA, President of the
Khronos Group and OpenCL Working Group Chair
“In recent years there has been an impressive adoption of OpenCL to drive
heterogeneous processing systems within many
market segments. This update to OpenCL 3.0 brings important flexibility benefits
that will allow many evolving
industries, from AI and HPC to automotive, to focus on their specific
requirements and embrace open standards. Codeplay
is excited to enable hardware vendors to support OpenCL 3.0 and to take
advantage of the flexibility provided in its
ecosystem of software products.”
Andrew Richards
Founder and CEO of Codeplay Software
“With its focus on deployment flexibility, we see OpenCL 3.0 as an
excellent step forward in providing critical features
for developers, with the ability to add functionality over time. This really is
a step forward for the OpenCL ecosystem,
allowing developers to write portable applications that depend on widely
accepted functionality. Currently shipping GPUs
based on the PowerVR Rogue architecture will enjoy a significant feature uplift
including SVM, Generic Address Space and
Work-group Functions. Upon final release of the specification, Imagination will
ship a conformant OpenCL 3.0
implementation with support extending across a wide range of PowerVR GPUs,
including our latest offering with IMG
A-Series.”
Mark Butler
Vice President of Software Engineering,
Imagination Technologies
“Intel strongly supports cross-architecture standards being driven across
the compute ecosystem such as in OpenCL 3.0 and
SYCL. Standards-based, unified programming models will enable efficiency and
unleash creativity for our developers with
the upcoming release of our new Xe GPU architecture.”
Jeff McVeigh
Vice President, Intel Architecture, Graphics
and Software
“NVIDIA welcomes OpenCL 3.0’s focus on defining a baseline to enable
developer-critical functionality to be widely
adopted in future versions of the specification. NVIDIA will ship a conformant
OpenCL 3.0 when the specification is
finalized and we are working to define the Vulkan® interop extension that,
together with layered OpenCL implementations,
will significantly increase deployment flexibility for OpenCL developers.”
Anshuman Bhat
Compute product manager at NVIDIA
“OpenCL 3.0 is an important step forward in the drive to unlock greater
performance and innovation across a broadening
range of computing platforms and applications. The flexible extension model will
help our customers and software
partners take full advantage of the tremendous potential available in both our
existing and future application
processors. We are pleased to have had the opportunity to contribute to this
specification and we look forward to
supporting the final product.”
Balaji Calidas
Director of Engineering at Qualcomm
“Many of our customers want a GPU programming language that runs on all
devices, and with growing deployment in edge
computing and mobile, this need is increasing. OpenCL is the only solution for
accessing diverse silicon acceleration
and many key software stacks use OpenCL/SPIR-V as a backend. We are very happy
that OpenCL 3.0 will drive even wider
industry adoption, as it reassures our customers that their past and future
investments in OpenCL are justified.”
Vincent Hindriksen
Founder and CEO of Stream HPC
“OpenCL 3.0 has opened up a new chapter for the OpenCL API which has served
as the standard GPGPU API during the past 10
years. With the streamlined OpenCL 3.0 core feature set, OpenCL 3.0 will enable
a whole new class of embedded devices to
adopt OpenCL API for GPU Compute and ML/AI processing, and it will also pave the
way forward for OpenCL to interop or
layer with the Vulkan API. VeriSilicon will deploy OpenCL 3.0 implementations
quickly on a broad range of our embedded
GPU and VIP products to enable our customers to develop new sets of GPGPU/ML/AI
applications with the OpenCL 3.0 API.”
Weijin Dai
Executive Vice President and GM of
Intellectual Property Division at VeriSilicon
Community
Join the OpenCL Community Discussions
There are several ways to follow the latest OpenCL developments, provide feedback on the
specification, and get your questions answered. It's a great way to get involved and will help forge
the future of OpenCL and the wider ecosystem.
Community Discussions
GitHub
Issues
and
Pull Requests
Khronos OpenCL Forum
Discord
Stack Overflow Questions
Help Shape the Future of OpenCL
If you are working with OpenCL and wish to get involved in helping shape its future, please consider
Joining Khronos and our Working Group. Any organization is welcome to join, and multiple levels of
membership are available to enable any organization, large or small, to get involved.
Join Khronos
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