In Association with
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| Date: |
January 24-27, 2012 |
| Location: |
205 108th Ave NE
Suite 400
Bellevue, WA 98004
Phone (425) 705-1900 |
| Contact: |
Acceleware
403.249.9099 x 356, services@acceleware.com |
| Cost: |
$3250 USD
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| Coupon Code: |
AXTEB2012 (Register by January 16, 2011 with this coupon code and receive a $250 discount!) |
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- 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
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Space is limited - Please register early to guarantee your spot
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For our hands-on exercises students will be working with Microsoft Visual Studio™ and NVIDIA® Parallel Nsight™.
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Your Instructor
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Kelly Goss - Software Developer – Trainer
Kelly is part of Acceleware’s software development and CUDA/OpenCL training team. She is also currently completing her PhD in Electrical Engineering at the University of Calgary. Her research is in the design of an optical detection system and data detection algorithms for a nanotechnology-based barcode system. Kelly has a M.Sc. in Electrical Engineering from the University of Calgary.
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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: Memory Performance Optimizations
- Lecture: Profiling CUDA/OpenCL Applications
- Hands-on-Exercise: Profiling CUDA/OpenCL Applications
- Lecture: Driver API
- Hands-on-Exercise: Driver API
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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
