Over at the Not Only Luck blog, John Melonakos describes why his company has chosen to open source ArrayFire GPU and accelerator software tools.
In this video, Bronson Messer from ORNL presents: An Introduction to OpenACC. “OpenACC is gaining momentum and adoption,” said Duncan Poole, President of the OpenACC Standards Group. “Developers benefit because using OpenACC directives makes parallel programming more productive and collaboration easier. Large, legacy codes are easier to maintain and accelerated code is more portable across HPC systems.”
This week Nvidia salutes Women who use CUDA for incredible science and engineering. They’ve compiled 30 profiles so far, and the advice they share from their experiences is quite inspiring. “It’s a good way to remind people that women write code, participate in open-source projects, and invent things,” said Lorena Barba from George Washington University. “It’s important to make the technology world more attractive to female students and show them examples of women who are innovators.”
Over at Typhoon Computing, Michel Müller writes programmers looking to port their code to accelerators now have a new tool called Hybrid Fortran. “This python-based preprocessor parses annotations together with your Fortran code structure, declarations, accessors and procedure calls, and then writes separate versions of your code – once for CPU with OpenMP parallelization and once for GPU with CUDA Fortran.”
“The use of GPUs to accelerate applications is mainstream nowadays, but their adoption in current high performance computing clusters is primarily impaired by the trend of including accelerators in all the nodes of the cluster, as this presents several drawbacks related with increased costs. In this talk we introduce the remote GPU virtualization mechanism, intended to address the drawbacks of GPU computing. The rCUDA remote GPU virtualization framework will also be presented.”