Accelerate Your Code Easily with OpenACC Directives

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ABOUT GPU COMPUTING

PARALLEL COMPUTING
WITH CUDA

GPU PROGRAMMING

OPENACC DIRECTIVES

KEPLER GPU ARCHITECTURE

Accelerate Your Scientific Code with OpenACC
The Open Standard for GPU Accelerator Directives

Hundreds of cores working for you

Based on the OpenACC standard, GPU directives are the easy, proven way to accelerate your scientific or industrial code. With GPU directives, you can accelerate your code by simply inserting compiler hints into your code and the compiler will automatically map compute-intensive portions of your code to the GPU. Here's an example of how easy a single directive hint can accelerate the calculation of pi. With GPU directives, you can get started and see results in the same afternoon.

By starting with a free, 30-day trial of CAPS directives today, you are working on the technology that is the foundation of the OpenACC directives standard. OpenACC is:

Easy: simply insert hints in your codebase.
Open: run the single codebase on either the CPU or GPU.
Powerful: tap into the power of GPUs within hours .

WHAT THE EXPERTS ARE SAYING

“At NOAA's Earth Systems Research Laboratory, we have been using CAPS HMPP for over two years to execute a single-source-code Numerical Weather Prediction (NWP) dynamical core on NVIDIA GPUs and on traditional CPUs. CAPS staff has been very helpful, quickly responding to help requests and even adding new features we have requested. For our code, the run-time performance of the CAPS compiler is very competitive with other commercial GPU compiler products. We look forward to upgrading from CAPS HMPP to OpenACC when the next version of our NWP code is finished this spring.”

Thomas Henderson, National Oceanic and Atmospheric Administration, USA

“I was searching tools to take advantage of GPU acceleration. CAPS OpenACC Compilers were my best choice because of their simple, easy and flexible usability. I strongly recommend scientists to use CAPS OpenACC compilers to concentrate on their study.”

Jin-Soo Kim from Konkuk University, South Korea

“We have been using CAPS OpenACC compilers in the context of porting and running production Applications to GPU. CAPS compilers have shown efficiency in productivity and performance. CAPS helped us by providing training and customer support. We are now extending CAPS licenses to the whole campus to allow all research groups to access GPUs.”

Alain CLO, KAUST (King Abdullah University of Science and Technology), Saudi Arabia

See more success stories »

Register for a 30-day CAPS trial license

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You'll need an NVIDIA® CUDA-capable GPU and a C or Fortran-based code to get started.