Skip to main content
“SYCL 2020’s primary goal is to achieve closer convergence with ISO C++, furthering our work to bring parallel heterogeneous programming to modern C++ through open standards. SYCL can leverage diverse processors to accelerate problems in many application domains including HPC, automotive, and machine learning,” said Michael Wong, Codeplay distinguished engineer, ISO C++ Directions Group and SYCL working group chair. “SYCL has a growing number of implementers and researchers working on real-world applications in markets ranging from supercomputing to embedded processing. The insights from that work, along with the feedback we collected from the SYCL 2020 provisional specification, has enabled the SYCL Working Group to deliver a feature-rich final specification that balances enhanced performance with backwards compatibility. I am excited by the simplicity and higher expressiveness offered by SYCL 2020 and we will continue to evolve SYCL to meet market needs.”
SYCL uses generic programming with templates and generic lambda functions to enable higher-level application software to be cleanly coded with optimized acceleration of kernel code across the extensive range of various acceleration APIs, such as OpenCL. Developers program at a higher level than the native acceleration API, but always have access to lower-level code through seamless integration with the native acceleration API through the interoperability mode, C/C++ libraries, and frameworks such as OpenCV™ or OpenMP™
SYCL implementations are available from an increasing number of vendors, including adding support for diverse acceleration API back-ends in addition to OpenCL:
The SYCL Academy repository provides materials that can be used for teaching SYCL. The materials are provided using the "Creative Commons Attribution Share Alike 4.0 International" license.Visit SYCL Academy
SYCL 2020 is the newest release of the SYCL specification, ratified by the Working Group in late 2020, published by the Khronos Group in early 2021. It follows SYCL 1.2.1, the last version to be based directly on OpenCL. Previous release followed OpenCL base release and In light of the move to a more generalized backend model as well as following ISO C++’s release based on year, the project has adopted a year-based versioning scheme.
SYCL 2020 represents a major step forward, featuring over 40 new additions and improvements, including:
“ Our users will benefit from features in the SYCL 2020 specification. New features, such as support for unified memory (USM) and reductions, are important capabilities for programming high-performance-computing hardware. In addition, support for C++17 will allow our users to write better C++ code, with both language features (such as deduction guides) and library features (such as std::optional). Other new features (such as softening the requirements on kernel functions and sharing data between host and devices) are an important step for implementing backend support for SYCL in the Kokkos and RAJA performance portability ecosystems. ”
“ At Cineca, based on our experience, we confirm the value that SYCL is bringing to the development of high-performance computing in a hybrid environment. In fact, through SYCL, it is possible to build a common and portable environment for the development of computing-intensive applications to be executed on HPC architectures configured with floating point accelerators, which allows industries and scientific communities to use the common availability of development tools, libraries of algorithms, accumulated experience. Cineca is already running the distributed Celerity runtime on top of several SYCL implementations on the new Marconi100 cluster, ranked no. 11 in the Top500, providing users with a unified API for both about 4000 NVIDIA Volta V100 GPUs and IBM Power9 host processors. SYCL 2020 is a big step towards a much leaner API that unlocks all the potential provided by modern C++ standards for accelerated data-parallel kernels, making the development of large-scale scientific software easier and more sustainable, either for industrial oriented domain applications for industries, either for scientific domain-oriented applications. ”
“ Codeplay has been deeply involved in SYCL from its original definition and we are now enabling the standard on a range of systems with our ComputeCpp product. We strongly believe SYCL is the only software standard to link all the high performance processors to a unified programming solution. Developers will find that SYCL 2020 refines the standard to streamline their development and adds some crucial new enhancements to improve productivity. ”
“ Imagination recognises the benefit of SYCL across multiple markets. Our software stacks have been designed to improve SYCL performance, enabling a straightforward path to exploit the teraflops of compute performance in our latest IP,. The ability to quickly port workloads from other proprietary APIs is a huge benefit, easing the transition from development on desktop to deployment on embedded systems. SYCL 2020 is a positive step forward for this API, enabling higher levels of performance, which will benefit developers and platform creators. ”
“ The SYCL 2020 final specification brings significant features to the industry that enable C++ developers to more productively build high-performance heterogeneous applications with unified programming across XPU architectures,. Several capabilities pioneered in the open source oneAPI C++/DPC++ compiler, such as unified shared memory, group algorithms, and sub-groups, contributed to this community effort. Open, cross-architecture programming is required for accelerated distributed computing; we look forward to continuing our collaboration to address the needs of the developer ecosystem. ”
“ With thousands of users and a wide range of applications using NERSC’s resources, we must support a wide range of programming models. In addition to directive-based approaches, we see modern C++ language-based approaches to accelerator programming, such as SYCL, as an important component of our programming environment offering for users of Perlmutter. Further, this work supports the productivity of scientific application developers and users through performance portability of applications between Aurora and Perlmutter. ”
“ NSITEXE supports the SYCL 2020 technology, which is gaining attention in embedded applications. SYCL is very important to increase productivity by hiding complexities from users. We are considering adopting this technology in our next generation of IP platforms. ”
“ For Renesas, SYCL is a key enabler for automotive ADAS/AD software developers that allows them to easily use the highly-efficient, heterogeneous accelerators of the R-Car SoC Series through the open Khronos standard. ”
“ We are excited about the extensive list of features and improvements released with the new SYCL 2020 specification. The API becomes terser and more developer friendly, while also introducing new ways for expert users to exercise fine-grained control over state-of-the-art hardware features. The move to a generalized backend model opens up new possibilities to integrate with existing legacy solutions, which is especially important in scientific research environments. As co-developers of the Celerity project, together with the University of Salerno, we are welcoming these changes and look forward to applying them within distributed-memory research and industry applications, for example as part of the recently launched EuroHPC LIGATE project. ”
“ Xilinx is excited about the progress achieved with SYCL 2020. This single-source C++ framework unifies host and device code for various kinds of accelerators in the same C++ program. With host-fallback device execution, developers can emulate device code on a CPU, exploring hardware-software co-design for adaptable computing devices. SYCL is now extensible via customizable back-ends, enabling device plug-ins for FPGAs and ACAPs. ”
SYCL 1.2.1 revision 7 is now the latest release as of April 27, 2020, is based on C++11 and OpenCL 1.2, and is a major update representing 5 years of work by Khronos members. The new specification incorporates significant experience gained from 5 separate implementations and feedback from developers of machine learning frameworks such as TensorFlow, which now supports SYCL alongside the original CUDA accelerator back-end.
SYCL 1.2.1 builds on the features of C++11, with additional support for C++14 and C++17, enabling ISO C++17 Parallel STL programs to be accelerated on OpenCL devices. To support this effort, Khronos is backing an open-source project to support Parallel STL on top of SYCL, running on OpenCL devices. This project is hosted on GitHub . So, while SYCL brings the power of single-source modern C++ to the OpenCL and SPIR world, it also prepares the convergence with other standards such as Khronos' Vulkan, OpenVX and NNEF and ISO C++ (SG1, SG6, SG12, SG14, SG19).
These SYCL 1.2 specification and conformance tests were released on May 11, 2015 and includes the following features: