“Accelerated Computing with NVIDIA Tesla and CUDA”

Location: A.V. Williams Building, Room 2120

Speaker:
Mark Harris
Chief Technologist for GPU Computing software, NVIDIA

Abstract:
In this talk you will learn about the NVIDIA Tesla accelerated computing platform, including the latest developments in NVIDIA GPU architecture and roadmap, how deep learning on GPUs is changing how we use computers to understand data, and the latest release of CUDA, NVIDIA’s parallel computing software platform and programming model.

I will discuss how new support for C++11 in CUDA 7, along with new features and performance improvements in the Thrust C++ parallel algorithms library and support for runtime compilation, makes parallel C++ more productive than ever. CUDA 7 also includes cuSOLVER, a new direct linear solver library, as well as new features and improved performance in other CUDA libraries.

Additionally, you will hear about these features and get insight into the philosophy driving the development of CUDA, and how it will take advantage of current and future GPUs.

Bio:
Mark Harris is the chief technologist for GPU Computing Software at NVIDIA, where he works as a developer advocate and helps drive NVIDIA’s GPU computing software strategy.

His research interests include parallel computing, general-purpose computation on GPUs, physically based simulation, and real-time rendering.

As a doctoral student at UNC Chapel Hill, Harris developed real-time cloud simulation and rendering software for GPUs (simulating clouds, not simulation in “the cloud”!).

In 2002, Harris recognized a nascent trend in computing and coined a name for it: GPGPU (General-Purpose computing on Graphics Processing Units), and founded GPGPU.org to provide a forum for those working in the field to share and discuss their work.