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Introduction to High-Performance GPU Architectures

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Course Summary

Home > Courses >Machine Learning Training >CUDA >Introduction to High-Performance GPU Architectures

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, students 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 students learning about optimization strategies.

The DevelopIntelligence remote lab environment 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
Hack-a-thon - Learning Spikes - Workshops
Duration
1 Day
Related Technologies
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  • Productivity 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.
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about our training

  • keywordicon1
    Real-World Content

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

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    Expert Practitioners

    Industry experts with 15+ years of industry experience that bring their battle scars into the classroom.

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    Experiential Learning

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

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    Fully Customized

    One-size-fits-all doesn't apply to training teams. That's where we come in!

What You'll Learn

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

  • Open CL/CUDA Programming Model
  • Stream Computing and SIMD Platforms
  • Threads and Thread Hierarchy
  • Memory Hierarchy
  • Synchronisation
  • Host and Device Interactions
  • GPU Device Architecture
  • Streaming Multiprocessors and Scalar Processors
  • On-chip Memory Registers and Local Shared Memory
  • Execution Model Warps Scheduling and Divergence
  • Device Memory and Latency
  • Performance Tuning and Optimization
  • Instruction Performance
  • Memory Access Patterns
  • Global Memory Coalescence
  • Local Memory Bank Conflicts
  • Optimization Strategies
Real-world content

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

Expert Practitioners

Industry experts that bring their battle scars into the classroom.

Experiential Learning

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

Fully Customized

One-size-fits-all doesn't apply to training teams. That's where we come in!

Elite Instructor Program

We recently launched our internal Elite Instructor Program. The community driven instructor program is designed to support instructors in transforming students’ lives by consistently showing a world-class level of engagement, ability, and teaching prowess. Reach out today to learn more about our instructors.

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DevelopIntelligence leads technical and software development learning programs for Fortune 500 companies. We provide learning solutions for hundreds of thousands of engineers for over 250 global brands.

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“I appreciated the instructor’s technique of writing live code examples rather than using fixed slide decks to present the material.”

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