When viewing the Technical Program schedule, on the far righthand side
is a column labeled "PLANNER." Use this planner to build your own
schedule. Once you select an event and want to add it to your personal
schedule, just click on the calendar icon of your choice (outlook
calendar, ical calendar or google calendar) and that event will be
stored there. As you select events in this manner, you will have your
own schedule to guide you through the week.
You can also create your personal schedule on the SC11 app (Boopsie) on your smartphone. Simply select a session you want to attend and "add" it to your plan. Continue in this manner until you have created your own personal schedule. All your events will appear under "My Event Planner" on your smartphone.
SESSION: M07: High Performance Computing with CUDA
EVENT TYPE: Tutorial
TIME: 8:30AM - 5:00PM
Presenter(s):Cyril Zeller, Paulius Micikevicius, Justin Luitjens, Vasily Volkov, Andrew Sheppard
ABSTRACT: CUDA is a general-purpose architecture for writing highly parallel applications. It provides several key abstractions – a hierarchy of thread blocks, shared memory, and barrier synchronization – for scalable high-performance parallel computing. Scientists throughout industry and academia use CUDA to achieve dramatic speedups on production and research codes. The CUDA architecture supports many languages, programming environments, and libraries including C/C++, Fortran, OpenCL, DirectCompute, Python, Matlab, FFT, LAPACK, etc.
In this tutorial NVIDIA engineers will partner with academics and industrials to present CUDA and discuss its advanced use for science and engineering domains. The morning session will teach the basics of CUDA C programming, give an overview of CUDA Fortran and the CUDA libraries, and discuss the main optimization techniques. The afternoon session will cover best practices for tuning and profiling CUDA programs and will close with two real-world case studies from academia and industry.
The only prerequisite for this tutorial is basic knowledge of C programming. No prior experience in GPU programming is required.
Cyril Zeller - NVIDIA
Paulius Micikevicius - NVIDIA
Justin Luitjens - NVIDIA
Vasily Volkov - University of California, Berkeley