In this tutorial, NVIDIA engineers and academic and industrial researchers will present CUDA and discuss its advanced use for science and engineering. The tutorial will demonstrate CUDA with traditional HPC examples including BLAS, FFT, and integration with Fortran and high-level languages (MATLAB, Mathematica, Python) and describe in detail the programming model at the heart of it all. It will then turn to advanced topics including optimizing CUDA programs, CUDA floating point performance and accuracy, and CUDA programming strategies and tips. Finally the tutorial will present detailed case studies in which domain scientists will describe their experience using CUDA to accelerate mature, deployed, real-world science codes. Scientists throughout industry and academia are already using CUDA to achieve dramatic speedups on production and research codes (see http://www.nvidia.com/cuda for a list of codes, academic papers and commercial packages based on CUDA). Presenters include Massimiliano Fatica (NVIDIA), Mark Harris (NVIDIA), Patrick LeGresley (NVIDIA), and Jim Phillips (UIUC). Follow this link to register.