OpenCL in Los Angeles, CA

Partnering with AMD, this professional four day course is designed for programmers who are looking to develop comprehensive skills in writing and optimizing applications that fully leverage data parallel processing capabilities of GPUs.

Your fee includes

  • Use of a laptop equipped with AMD Fusion APU
  • Choice of Linux or Windows operating system
  • Printed manual of all lectures
  • Electronic copy of lab exercises
  • OpenCL Quick Reference Guide
  • Certificate of Completion
  • Beverages and snacks

Space is limited - Please register early to guarantee your spot

Your Instructor

Kelly Goss - Training Program Manager
Kelly is the Training Program Manager for Acceleware. She has taught over 25 parallel programming courses for students from a diverse range of industries and backgrounds. Kelly is also a member of Acceleware’s development team, assisting in the writing and optimization of Acceleware applications and providing consulting services to our clients. Kelly has a PhD in Electrical Engineering from the University of Calgary.

Schedule

Tue and Wed: 9:00AM – 5:00PM (includes a 1 hour break for lunch)
 

Agenda

  • 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

Registration has been closed.

Course details

Date:Apr 9 to Apr 12, 2013
Registration closes:Mar 24, 2013 at 7:45PM (MST)
Location:Los Angeles, CA
Cost:$3,250 USD

 

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