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CUDA Training in Baltimore/Washington


Monday, March 4, 2013 at 9:00 AM - Tuesday, March 5, 2013 at 5:00 PM

CUDA Training in Baltimore/Washington

Ticket Information

Ticket Type Sales End Price Fee Quantity
CUDA-TRAINING-2DAY Ended $1,399.00 $0.00

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Event Details

GPU acceleration is awesome, but writing fast CUDA can be challenging. This comprehensive two day course will enable you to become proficient in writing and optimizing applications for GPU acceleration.

Partnering closely with NVIDIA, AccelerEyes CUDA training courses are the fastest way for you to become proficient at CUDA programming for NVIDIA GPUs. AccelerEyes is uniquely equipped to provide training for NVIDIA CUDA GPUs due to our extensive experience programming ArrayFire. We have helped thousands of organizations speedup their code and our primary objective is to help you increase productivity while maximizing the return on your hardware.

Course Goodie Bag

All training courses include the following:

  • Instruction by an excellent and interesting expert. Many hands-on exercises
  • Use of a laptop with CUDA capable GPU
  • Choice of Linux or Windows operating system
  • Printed manual of lecture material
  • Electronic copy of programming exercises
  • Certificate of Completion 

CUDA Training Course Syllabus

Day 1: Introduction to CUDA

  • GPU Computing Overview
  • The CUDA Programming Model
  • Basic Dataset Mapping Techniques
  • CUDA Libraries, ArrayFire
  • Asynchronous Operation
  • Profiling Tools


  • A Simple CUDA Kernel
  • Equivalent ArrayFire Example
  • Using CUDA Libraries
  • Monte Carlo Pi Estimation
  • Timing CUDA and ArrayFire
  • Debugging CUDA Code

Day 2: CUDA Optimization

  • CUDA Architecture: Grids,Blocks,and Threads
  • CUDA Memory Model: Global,Shared and Constant Memory
  • Advanced Mapping Techniques
  • CUDA Streams: Asynchronos Launches and Concurrent Execution
  • ArrayFire: Lazy Evaluation and Code Vectorization


  • Matrix Transpose
  • Optimization Using Shared Memory
  • Median Filter
  • Optimization Using Constant Memory
  • CUDA Stream Example
  • ArrayFire Example: Nearest Neighbor Algorithm
Have questions about CUDA Training in Baltimore/Washington? Contact AccelerEyes

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