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Introduction to High-Performance GPU Architectures

Course Summary

The Introduction to High-Performance GPU Architectures training course introduces the programming techniques required to develop general purpose software applications for GPU hardware.

The course begins by examining the programming models of both OpenCL and NVIDIA's CUDA development framework. Next, participants will learn how GPU hardware architectures differ from traditional CPU architectures and the changes in the programming environment (development, debugging, and validation). The course concludes with participants learning about optimization strategies.

The lab environment for this course utilizes Nvidia hardware (Nvidia GTX480 and Tesla C2070) to illustrate CUDA/OpenCL concepts and to allow training participants to experimentally investigate performance issues, debugging techniques, and code examples.

Purpose
Learn about CUDA programming, profiling, and debugging techniques required to develop general purpose software applications for GPU hardware
Audience
Software developers who need to implement high performance applications (e.g. numerical computing areas: finance and engineering)
Role
Software Developer
Skill Level
Intermediate
Style
Lecture | Hands-on Activities | Labs
Duration
1 Day
Related Technologies
CUDA

 

Learning Objectives
  • Describe programming models of both OpenCL and NVIDIA's CUDA development framework
  • Explore how GPU hardware architectures differ from traditional CPU architectures
  • Evaluate CUDA programing, profiling and debugging techniques

What You'll Learn:

In the Introduction to High-Performance GPU Architectures training course, you'll learn:

Programming and Execution Models

  • Open CL/CUDA Programming Model
  • Stream Computing and SIMD Platforms
  • Host and Device Interactions
  • Threads and Thread Hierarchy
  • Execution Model Warps Scheduling and Divergence

GPU Architecture and Hardware

  • GPU Device Architecture
  • Streaming Multiprocessors and Scalar Processors
  • On-chip Memory Registers and Local Shared Memory
  • Memory Hierarchy
  • Device Memory and Latency

Synchronization and Memory Optimization

  • Synchronisation
  • Memory Access Patterns
  • Global Memory Coalescence
  • Local Memory Bank Conflicts

Performance Tuning and Optimization

  • Performance Tuning and Optimization
  • Instruction Performance
  • Optimization Strategies
real world content

Real-World Content

Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
expert practitioners

Expert Practitioners

Industry experts that bring their battle scars into the classroom.
experiential learning

Experiential Learning

More coding than lecture, coupled with architectural and design discussions.
tailored outlines

Tailored Outlines

One-size-fits-all doesn't apply to training teams. That's where we come in!
“I appreciated the instructor's technique of writing live code examples rather than using fixed slide decks to present the material.”

VMware

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