GPU Programming Fundamentals Training in San Francisco

GPU Programming Fundamentals Training in San Francisco, USA

Participants will gain foundational knowledge in writing parallel algorithms, managing GPU memory, and optimizing code performance for GPU execution.

Enroll Now

GPU Programming Fundamentals Training is a professional training program delivered by ProgNXT in San Francisco, USA. ProgNXT, a globally recognized corporate training provider in 55+ countries, offers this GPU Programming Fundamentals Training course with hands-on, instructor-led sessions. This course introduces the core principles of GPU programming, including GPU architecture, parallel programming concepts, and hands-on development...

Expert Panel

Designed and delivered by the ProgNXT Programming Expert Panel — a vetted team of industry professionals with 14+ years of hands-on experience in Python, Java, C++, and full-stack application development

ProgNXT Programming Expert Panel

Course Code: UHV50
21 Hrs
Last Updated: April 2026

Course Rating5/5

This course introduces the core principles of GPU programming, including GPU architecture, parallel programming concepts, and hands-on development with CUDA C/C++. Participants will gain foundational knowledge in writing parallel algorithms, managing GPU memory, and optimizing code performance for GPU execution.

Welcome to the official GPU Programming Fundamentals Training certification program in San Francisco, USA. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge locally. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 21 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

Basic knowledge of C or C++ programming
Familiarity with operating systems and command-line usage
No prior experience with GPU programming required

By the end of this course, participants will:

Have a strong understanding of GPU and CUDA fundamentals
Be able to write simple, functional CUDA programs
Understand how to utilize parallelism in algorithm design
Know how to debug, profile, and optimize GPU code
Be prepared for further exploration into HPC, ML, and advanced GPU topics

Understand GPU architecture and execution model
Write and launch CUDA kernels
Manage GPU memory and data transfer
Debug and optimize parallel code
Analyze performance and implement simple parallel algorithms

CUDA kernel structure and grid configuration
GPU memory types and access patterns
Thread synchronization and control
Profiling and analyzing GPU performance
Basic parallel algorithms (e.g., vector addition, reduction)

ProgNXT Certificate of Completion will be awarded to participants who complete the course and pass the evaluations.

INTRODUCTION TO GPU COMPUTING AND CUDA

Introduction to GPU Architecture

Why GPU computing? CPU vs GPU comparison

CUDA architecture: cores, warps, blocks, and grids

Execution model and SIMT (Single Instruction Multiple Thread)

Getting Started with CUDA Programming

CUDA development tools and environment setup

Writing and compiling a basic CUDA program

Anatomy of a CUDA kernel and launch configuration

GPU MEMORY MODEL AND THREADING

Understanding GPU Memory Hierarchy

Global, shared, constant, and local memory

Memory coalescing and access patterns

Performance impact of memory usage

Thread Organization and Synchronization

Thread indexing in CUDA

Synchronizing threads with __syncthreads()

Avoiding race conditions and deadlocks

PERFORMANCE OPTIMIZATION AND APPLICATIONS

Debugging and Profiling CUDA Applications

Using tools like nvprof, Nsight Compute, and cuda-memcheck

Identifying and fixing performance bottlenecks

Measuring speed-up and efficiency

Implementing Parallel Algorithms

Parallel reduction techniques

Matrix multiplication and stencil operations

Real-world use cases: image processing, simulations

Final Hands-On and Wrap-Up

Review, Q&A, and recommended learning paths

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants will be evaluated based on:
Daily quizzes, mock questions and query resolution. Participation in hands-on exercises and labs. Performance in the final review and hands-on exercises will be evaluated.
ProgNXT Certificate of Completion will be awarded to participants who complete the course and pass the evaluations.

GPU Programming Fundamentals Training Events in san-francisco

Online Events

Global Region	Location	Start Date	End Date	Action
‌	‌	‌	‌	‌
‌	‌	‌	‌	‌
‌	‌	‌	‌	‌
‌	‌	‌	‌	‌
‌	‌	‌	‌	‌

More Upcoming Session Dates

October 2026

📍 San Francisco, USA

11th Oct 2026→13th Oct 2026

📍 San Francisco, USA

23rd Oct 2026→25th Oct 2026

🌐 Online Instructor-Led

23rd Oct 2026→25th Oct 2026

November 2026

📍 San Francisco, USA

8th Nov 2026→10th Nov 2026

🌐 Online Instructor-Led

11th Nov 2026→13th Nov 2026

📍 San Francisco, USA

24th Nov 2026→26th Nov 2026

🌐 Online Instructor-Led

28th Nov 2026→30th Nov 2026

December 2026

📍 San Francisco, USA

5th Dec 2026→7th Dec 2026

🌐 Online Instructor-Led

8th Dec 2026→10th Dec 2026

📍 San Francisco, USA

18th Dec 2026→20th Dec 2026

🌐 Online Instructor-Led

18th Dec 2026→20th Dec 2026

Events for other courses in San Francisco, USA

Global Region	Course Name	Start Date	End Date	Action
‌	‌	‌	‌	‌
‌	‌	‌	‌	‌
‌	‌	‌	‌	‌
‌	‌	‌	‌	‌
‌	‌	‌	‌	‌

GPU Programming Fundamentals Training in San Francisco