• Use of a laptop equipped with AMD Fusion APU
• Manual of all lectures
• CD copy of lab exercises
• OpenCL Quick Reference Card
• Certificate of Completion

Kelly Goss - Software Developer – Trainer

Kelly is part of Acceleware’s software development and CUDA/OpenCL training team. She is also currently completing her PhD in Electrical Engineering at the University of Calgary. Her research is in the design of an optical detection system and data detection algorithms for a nanotechnology-based barcode system. Kelly has a M.Sc. in Electrical Engineering from the University of Calgary.

• Day 1: Introduction to GPU Programming and GPU Architectures
  • Overview of GPU Computing
  • OpenCLL Software
  • Data-Parallel Architectures and the OpenCL Programming Model
  • The OpenCL Memory Model & Work-item Cooperation
  • Hands-on-Exercises: Buffer Allocation and Buffer Transfers, Simple Kernels and Local and Constant Memory
• Day 2: Advanced GPU Programming and Debugging
  • Task Concurrency and Synchronization
  • Images and Graphics Interoperability
  • Debugging GPU Programs and Numerical Accuracy
  • Hands-on-Exercises: Asynchronous Operations, Images and Graphics Interoperability and Debugging
• Day 3: Introduction to Optimizations
  • Latency and the Execution Model
  • Arithmetic Optimizations
  • Memory Optimizations
  • Hands-on-Exercises: Arithmetic Optimizations and Correcting memory access pattern transfers and local memory bank conflicts
• Day 4: Advanced Optimizations and Profiling
  • Profiling applications
  • Case Study – 3D Convolution or Other Case Study
  • Multiple GPUs, Cluster of GPUs
  • Hands-on-Exercises: Using the Stream Profiler to optimize a kernel and 3D Convolution – Putting it all together