Nvidia has announced two major initiatives with European universities: the University of Manchester in the UK has become a Cuda Research Centre, while the Swiss Federal Institute of Technology in Zurich (ETH Zurich) is to establish an Nvidia Co-Design Lab for Hybrid Multicore Computing.
The Cuda Research Centre award will provide Manchester researchers and students with access to Nvidia experts as well as the latest hardware, so that its graduates can acquire the knowledge and tools needed to take advantage of the parallel processing power of GPUs. Free teaching kits, textbooks, software licences, GPUs for lab computers, and academic discounts for additional hardware will be available as a result of the initiative. Manchester already has a ‘GPU Club’ – a group of some 300 researchers who exchange ideas on how best to use GPUs and other emerging technology. There are now 336 Cuda Research Centres worldwide.
One of the aims of the ETH Co-Design Lab for Hybrid Multicore Computing is to encourage closer collaboration between computing system architects, integrators, application developers, and researchers, so that they can exchange ideas and experiences. The ultimate objective is to speed up the design of new applications and technologies. At first, the lab will focus on six scientific domains: meteorology and climate; geophysics; materials science and nanotechnology; life science; astro- and plasma-physics; as well as biomedical engineering and fluid mechanics.
The ETH lab’s hybrid multicore supercomputer couples high-performance, energy-efficient GPU accelerators with CPUs. The new lab will give students and scientists access to GPU-based supercomputing systems and programming environments and Nvidia will be offering hands-on training, and the latest tools and resources, to help scientists tune their research for current and GPU-accelerated supercomputers. The Swiss National Supercomputing Centre (CSCS) in Lugano will collaborate closely with the lab, supplying computing resources and technical expertise to help domain scientists get running quickly and efficiently.
