GPU acceleration of scientific applications: An update

<!--HTML--><p align="justify"> Just five years ago, NVIDIA introduced CUDA, the Compute Unified Device Architecture, which significantly simplified the development of scientific applications on Graphics Processing Units (GPUs). Since these early days of CUDA, both GPU hardware and software have made tremendous progress in terms of programmability and ease of use, allowing an ever increasing set of applications to benefit from GPUs. Especially the latest generation of NVIDIA GPUs, Kepler, introduced many features geared towards HPC applications and to ensure high performance and ease of use.</p> <p align="justify"> In this seminar, we will give an overview of the Kepler architecture, present the new features of CUDA 5 and show how they can be used to accelerate scientific applications. In addition, we will present CARMA, the CUDA on ARM development board hosting a NVIDIA Tegra CPU and CUDA GPU, and show how to use these boards to explore an exciting high-performance, low power consumption node architecture. </p> <h4>About the speakers</h4> <b>Edmondo Orlotti - HPC Development Manager</b> <p align="justify"> Edmondo Orlotti is responsible for the business development of NVIDIA HPC Solutions in Southern Europe, for Education and Research. He joined NVIDIA in 2005 as marketing manager for the same region, then moving in 2008 to the professional solutions division. He's been addressing advanced visualization needs of industrial and academic environments, integrating the portfolio of NVIDIA technologies with the local contexts of users needs. </p> <b>Peter Messmer - Senior Devtech Engineer</b> <p align="justify"> Peter joined NVIDIA in 2011 after spending more than 15 years developing HPC and GPU accelerated applications for industry and Government clients, mainly in the area of plasma and EM simulations, data analysis and visualization. In his role as Senior Devtech Engineer at NVIDIA, Peter is working with HPC users around the globe supporting them in accelerating their scientific discovery process by taking advantage of GPUs in their applications. Peter holds and MSc and PhD in Physics from ETH Zurich, Switzerland, with specialization in kinetic plasma physics and non-linear optics.</p>