This free webinar series will be offered live with two different sessions at two different times. In the event that you cannot attend during those times, we will also offer recorded copies of those sessions. The first session starts on April 15th, so don't delay!
This series will cover the basics of data parallel computing on GPU’s leveraging NVIDIA’s CUDA architecture . Tutorials will cover many topics including C for CUDA, programming to the OpenCL API , using Direct X Compute, and performance optimization techniques. These sessions will be presented by NVIDIA Developer Technology Engineering team.
Pre-registration is required if you wish to attend the live event. Please follow the links provided and registration details will be emailed back if your registration is successful.
Session 1: GPU Computing – An Introduction, 1.5 Hours + Q&A
Ideal for developers new to GPU computing, this will cover an introduction to the basics of GPU computing using the NVIDIA CUDA technology. Concepts will be illustrated with step-by-step walkthroughs of code samples, which can be readily compiled and run. Little or no prior GPU Computing experience isrequired. Topics covered include:
- Writing a small GPU computing program in C from scratch
- Data transfers
- Executing functions on the GPU
- Taking advantage of on-chip shared memory
- Coordinating CPU and GPU execution
Session Dates for "GPU Computing – An Introduction" (follow links to register)
Session 2: Performance Considerations for CUDA Programming 1.5 hour + Q&A
This is a more advance session on GPU computing and optimization considerations. Concepts will be illustrated using real code examples together with actual performance gains. Attendance of the “GPU Computing – An introduction” tutorial or some experience programming using CUDA Technology is a recommended preparation for this session. Topics covered include:
- Basic optimization techniques
- Performance measurement
- Getting the most out of CUDA’s memory system
- Execution configurations.
Session Dates for "Performance Considerations for CUDA Programming" (follow links to register)
Posted on 04/13/2009
