CUDA in San Jose, CA

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

Your fee includes

  • Use of a laptop equipped with CUDA capable GPU
  • Choice of Windows and Linux OS
  • Printed manual of all lectures
  • Electronic copy of lab exercises
  • 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

Mon-Thu: 9:00AM – 5:00PM (includes a 1 hour break for lunch)
 

Agenda

  • Day 1:
    • Overview of GPU computing
    • Data-parallel architectures and the GPU programming model
    • GPU memory model & thread cooperation
    • Hands-on exercises: GPU memory management, simple CUDA kernels and shared memory and constant memory
  • Day 2:
    • Asynchronous operations
    • Advanced CUDA features
    • Libraries
    • Debugging GPU Programs
    • Hands-on-exercises: Asynchronous operations, CUDA features, experience with CUFFT, CUBLAS, Thrust, debugging
  • Day 3:
    • Introduction to optimization
    • Resource management, latency and occupancy
    • Memory performance optimizations
    • Profiling applications
    • Hands-on exercises: Arithmetic optimizations, occupancy calculator, profiling and memory access patterns
  • Day 4:
    • CUDA compiler and user-defined libraries
    • OpenACC
    • Hands-on exercises: Case study exercise and OpenACC
    • Case study: Finite difference stencil algorithm or monte carlo simulations

All lectures are a combination of teaching and hands-on tutorials

NVIDIA’s foundational training material is augmented with Acceleware’s experience over the past 8 years and with examples specific to an HPC audience

Online registration is now closed.

Course details

Date:Jul 29 to Aug 1, 2013
Registration closes:Jul 15, 2013 at 7:15PM (MST)
Location:San Jose, CA (venue TBC)
Cost:$3,250 USD

 

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