GPGPU Programming

Students learn with interactive and hands-on sessions about GPU hardware, GPU languages, discovering how best to take advantage of GPUs for their computational needs. The course covers programming in both OpenCL and CUDA, pointing out the similarities and differences along the way. Topics include both the core languages and extensions including those for double precision and interfacing with OpenGL 3D graphics buffers.

Topics

• Introduction to GPGPU
• Compiling OpenCL and CUDA
• Host-side APIs
• OpenCL and CUDA Device Languages
• Memory Model
• Execution Model
• Synchronization
• Error Handling
• Profiling
• GPGPU Idioms
• Multi-GPU systems
• Application Case Studies

Objectives

Upon completion of this course, the student will:

• Understand modern GPGPU architectures and how to map their computational algorithms to GPUs
• Write programs using either OpenCL or CUDA
• Optimize GPGPU programs for their target hardware