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
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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.
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Schedule
Tue-Fri: 9:00AM – 5:00PM (includes a 1 hour break for 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 8 years and with examples specific to an HPC audience
