July 31, 2013
“OpenMP 4.0 is a major advance that adds two new forms of parallelism in the form of device constructs and SIMD constructs," stated Bronis R. de Supinski, Chair of the OpenMP Language Committee. “It also includes several significant extensions for the loop-based and task-based forms of parallelism already supported in OpenMP 3.1.”
Standard for parallel programming extends its reach
With this release, OpenMP, 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. OpenMP 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 included in OpenMP 4.0
"This release represents collaborative work by many of the brightest in industry, research, and academia, and it builds on the consensus of 26 members. We strive to deliver high-level parallelism that is portable across three widely-implemented common General Purpose languages, that is productive for HPC and consumers, and that delivers highly competitive performance,” says Michael Wong, CEO of the OpenMP ARB. “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. After this release, OpenMP will move immediately forward to the next release to bring even more usable parallelism to everyone."
The OpenMP Application Program Interface (API) is a multi-platform shared-memory parallel programming model for the C, C++ and Fortran programming languages. Jointly defined by a group of major computer hardware and software vendors and the user community, OpenMP is a portable, scalable model that gives shared-memory parallel programmers a simple and flexible interface for developing parallel applications for platforms ranging from multicore systems and SMPs, to embedded systems.
10/30/2013 | Cray, DDN, Mellanox, NetApp, ScaleMP, Supermicro, Xyratex | Creating data is easy… the challenge is getting it to the right place to make use of it. This paper discusses fresh solutions that can directly increase I/O efficiency, and the applications of these solutions to current, and new technology infrastructures.
10/01/2013 | IBM | A new trend is developing in the HPC space that is also affecting enterprise computing productivity with the arrival of “ultra-dense” hyper-scale servers.
Ken Claffey, SVP and General Manager at Xyratex, presents ClusterStor at the Vendor Showdown at ISC13 in Leipzig, Germany.
Join HPCwire Editor Nicole Hemsoth and Dr. David Bader from Georgia Tech as they take center stage on opening night at Atlanta's first Big Data Kick Off Week, filmed in front of a live audience. Nicole and David look at the evolution of HPC, today's big data challenges, discuss real world solutions, and reveal their predictions. Exactly what does the future holds for HPC?