In Association with
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| Date: |
May 8-11, 2012 |
| Location: |
Calgary, AB |
| Contact: |
Acceleware
403.249.9099 x 356, services@acceleware.com |
| Cost: |
$3250 USD
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- Use of a laptop equipped with CUDA capable GPU
- Manual of all lectures
- CD 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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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
