CUDA in New York, NY - Finance Focus

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 Accceleware applications and providing consulting services to our clients. Kelly has a PhD in Electrical Engineering from the University of Calgary.


Tue-Fri: 9:00AM – 5:00PM (incl. 1 hour lunch)


  • Day 1:
    • Lecture: Overview of GPU Computing
    • Hands-on-Exercise: Memory Allocation and Memory Transfers
    • Lecture: Data-Parallel Architectures and the CUDA Programming Model
    • Hands-on-Exercise: Simple Kernels
    • Lecture: The CUDA Memory Model & Thread Cooperation
    • Hands-on-Exercise: Shared Memory and Constant Memory
  • Day 2:
    • Lecture: Textures
    • Hands-on-Exercise: Textures
    • Lecture: Asynchronous Operations
    • Hands-on-Exercise: Asynchronous Operations
    • Lecture: Other GPU Features
    • Lecture: CUDA Libraries
    • Hands-on-Exercise: CUDA Libraries
  • Day 3:
    • Lecture: Debugging Tools and Techniques
    • Hands-on-Exercise: Debugging Tools and Techniques
    • Lecture: Introduction to Optimization
    • Hands-on-Exercise: Arithmetic Optimization
    • Lecture: Resource Management, Latency and Occupancy
    • Hands-on-Exercise: Occupancy Calculator
  • Day 4 :
    • Lecture: Memory Performance Optimizations
    • Hands-on-Exercise: Memory Performance Optimizations
    • Lecture: Profiling CUDA/OpenCL Applications
    • Hands-on-Exercise: Profiling CUDA/OpenCL Applications
    • Lecture: Driver API
    • Hands-on-Exercise: Driver API

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:Dec 4 to Dec 7, 2012
Registration closes:Nov 20, 2012 at 4:15PM (MST)
Location:1230 Avenue of the Americas
Rockefeller Center, 7th Floor
New York City, New York, 10020
Tel: +1 212 618 6310
Cost:$3,250 USD


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