OpenACC Blog

The Gaia mission is an extraordinarily large project launched by the European Space Agency (ESA) in 2013 to create the most precise 3D map of the Milky Way, describing the position, motion, and properties of nearly two billion objects. The Gaia Astrometric Verification Unit–Global Sphere Reconstruction (AVU–GSR) Parallel Solver derives the positions and proper motions of primary stars in the Milky Way observed with the Gaia satellite.

Understanding turbulent fluid flows lies at the heart of such versatile domains as climate, health, and energy. Modern methods used in flow simulations have yet to reach their efficiency limits in providing fast, high-resolution predictions. To answer outstanding questions about the nature of turbulence requires massive computing power and innovative  methods designed with computational efficiency at their core.

The field of computational fluid dynamics (CFD) struggles with challenges to resolve computational complexity and cost of the simulations. Executing the operations over large fine meshes at small timesteps requires the algorithms to be designed with parallel efficiency at their core. 

Climate scientists writing code have often been weary of multithreading, both on CPU and GPU, due to some aspect of non-reproducibility, across machines and implementations. However, the current state of the ICON model, with about 2 Million lines of code written since 2001, is living proof that porting legacy software to GPUs can be made possible with compiler directives.

The recent Open Accelerated Computing Summit (OAC Summit) brought together researchers and developers from around the world, sharing significant OpenACC updates and use cases and highlighting relevant modeling, simulation, and AI initiatives advanced by the Open Hackathons program. 

The number of available accelerators featured in high-performance computing (HPC) systems is rapidly increasing. As this trend continues, compute nodes are expected to become more heterogeneous and complex than ever before. Consequently, applications will require the right set of programming models and tools to program these systems to take full advantage of their massive performance. Thus, it is important to answer the question of how to provide performance, portability, and programmability in current and future HPC systems and applications.

Another year has passed since the release of OpenACC 3.2 and, once again, the technical committee has been hard at work maintaining and improving the OpenACC specification. As a committee we decided several years ago that an annual release cadence is the best way to ensure that improvements are delivered in a thoughtful and timely manner.

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NVIDIA’s GPU Technology Conference (GTC) kicks off next week, ushering in four days of discovery that promises to be one of the premier developer conferences for 2022.  This virtual conference—which takes place from March 21-24—brings together preeminent speakers from every walk of academia, research and industry to share how the latest technology and tools are shaping scientific advancement.

It’s been a year since we announced the completion of OpenACC 3.1 and I’m pleased to announce that we have now completed version 3.2. For the past several OpenACC releases we have taken the approach of releasing on an annual cadence so that our releases aren’t held up by unfinished business and so that our implementers don’t have to read and understand monolithic changes upon release. It’s sometimes heard on OpenACC technical calls that we’d rather miss a release to get the feature right than hold up releasing things that are complete just to finish one more thing.

Delve deeper into breakthroughs fueled by the most transformative technologies of our time.

NVIDIA’s GPU Technology Conference (GTC) is right around the corner, promising to be one the premier conferences of 2021.