The OpenMP 4.0 API Specification is released with Significant New Standard Features
The OpenMP 4.0 API supports the programming of accelerators, SIMD programming, and better optimization using thread affinity
The OpenMP Consortium has released OpenMP API 4.0, a major upgrade of the OpenMP API standard language specifications. Besides several major enhancements, this release provides a new mechanism to describe regions of code where data and/or computation should be moved to another computing device.
Bronis R. de Supinski, Chair of the OpenMP Language Committee, stated that “OpenMP 4.0 API is a major advance that adds two new forms of parallelism in the form of device constructs and SIMD constructs. It also includes several significant extensions for the loop-based and task-based forms of parallelism already supported in the OpenMP 3.1 API.”
The 4.0 specification is now available on the
Standard for parallel programming extends its reach
With this release, the OpenMP API specifications, the de-facto standard for parallel programming on shared memory systems, continues to extend its reach beyond pure HPC to include DSPs, real time systems, and accelerators. The OpenMP API aims to provide high-level parallel language support for a wide range of applications, from automotive and aeronautics to biotech, automation, robotics and financial analysis.
New features in the OpenMP 4.0 API include:
· Support for accelerators. The OpenMP 4.0 API specification effort included significant participation by all the major vendors in order to support a wide variety of compute devices. OpenMP API provides mechanisms to describe regions of code where data and/or computation should be moved to another computing device. Several prototypes for the accelerator proposal have already been implemented.
· SIMD constructs to vectorize both serial as well as parallelized loops. With the advent of SIMD units in all major processor chips, portable support for accessing them is essential. OpenMP 4.0 API provides mechanisms to describe when multiple iterations of the loop can be executed concurrently using SIMD instructions and to describe how to create versions of functions that can be invoked across SIMD lanes.
· Error handling. OpenMP 4.0 API defines error handling capabilities to improve the resiliency and stability of OpenMP applications in the presence of system-level, runtime-level, and user-defined errors. Features to abort parallel OpenMP execution cleanly have been defined, based on conditional cancellation and user-defined cancellation points.
· Thread affinity. OpenMP 4.0 API provides mechanisms to define where to execute OpenMP threads. Platform-specific data and algorithm-specific properties are separated, offering a deterministic behavior and simplicity in use. The advantages for the user are better locality, less false sharing and more memory bandwidth.
· Tasking extensions. OpenMP 4.0 API provides several extensions to its task-based parallelism support. Tasks can be grouped to support deep task synchronization and task groups can be aborted to reflect completion of cooperative tasking activities such as search. Task-to-task synchronization is now supported through the specification of task dependency.
· Support for Fortran 2003. The Fortran 2003 standard adds many modern computer language features. Having these features in the specification allows users to parallelize Fortran 2003 compliant programs. This includes interoperability of Fortran and C, which is one of the most popular features in Fortran 2003.
· User-defined reductions. Previously, OpenMP API only supported reductions with base language operators and intrinsic procedures. With OpenMP 4.0 API, user-defined reductions are now also supported.
· Sequentially consistent atomics. A clause has been added to allow a programmer to enforce sequential consistency when a specific storage location is accessed atomically.
This represents collaborative work by many of the brightest in industry, research, and academia, building on the consensus of 26 members. We strive to deliver high-level parallelism that is portable across 3 widely-implemented common General Purpose languages, productive for HPC and consumers, and delivers highly competitive performance. I want to congratulate all the members for coming together to create such a momentous advancement in parallel programming, under such tight constraints and industry challenges.
With this release, the OpenMP API will move immediately forward to the next release to bring even more usable parallelism to everyone. – Michael Wong, CEO OpenMP ARB.