MATLAB® is a high-level language and interactive environment for algorithm development, data analysis, visualization, and numerical computation.
In this webinar you’ll see how MATLAB supports the CUDA development process by providing a high-level language for testing CUDA kernels and prototyping algorithms on the GPU. You’ll learn to integrate your CUDA kernels into MATLAB applications and write test harnesses to validate that your kernels are working correctly – a task that can often be time consuming and tedious. In addition, you will also see how MATLAB’s GPU-enabled functionality lets you take advantage of GPU computing without having to use low-level GPU computing libraries or learn the intricacies of GPU architectures.
Product demonstrations will highlight how you can:
Previous MATLAB knowledge is not required for this webinar.
A Q&A session will follow the presentation.
About the Presenters:
Daniel Armyr, MathWorks
Daniel holds a M.Sc. in Engineering Physics from KTH Royal Institute of Technology. He has worked 6 years with product development and MATLAB modeling in the medical device industry. He joined the Application Engineering team at MathWorks in February 2012. Before that he worked one year as a consultant, modeling the analog electronics in eddy-current systems. He now specializes in high performance computing and parallel computation.
Jonathan Bentz, NVIDIA
Jonathan Bentz is a Solution Architect with NVIDIA, focusing on Higher Education and Research customers. Prior to NVIDIA Jonathan worked for Cray as a software engineer in the Scientific Libraries group working on dense linear algebra and FFT software. Jonathan obtained a PhD in physical chemistry and an MS in computer science from Iowa State University.