CUDA Training Course in New York, NY - Finance Focus

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In Association with

Acceleware CUDA Training in Association with Microsoft
Date: December 4-7, 2012
Location: New York, NY
Contact: Acceleware
403.249.9099 x 356, services@acceleware.com
Cost: $3250 USD
Early Bird Offer: Register before Nov 13th, 2012 and receive $200 off the registration fee! (enter discount code: AXTEB2012)
 

 
This 4 day CUDA training course has a finance flavor and the hands-on exercise you will be working on for day 4 features an application of CUDA in the field. A background in finance is not necessary.

 
Your fees include:

  • Use of a laptop equipped with CUDA capable GPU
  • Manual of all lectures
  • Electronic copy of lab exercises
  • Certificate of Completion
  • Morning beverages (coffee, tea, juices) and afternoon snacks

Space is limited - Please register early to guarantee your spot
 

Microsoft Visual Studio For our hands-on exercises students will be working with Microsoft Visual Studio™ and NVIDIA® Parallel Nsight™. NVIDIA Parallel Nsight

Schedule

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

Agenda

  • 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: Monte Carlo Case Study
    • Lecture: Profiling CUDA Applications
    • Hands-on-Exercise: Profiling CUDA 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 7 years and with examples specific to an HPC audience