GPU Programming Classroom Training and Certification
Course Overview
- Course Rating 4.5/5
Overview
This GPU Programming training program provides a comprehensive introduction to GPU programming, focusing on leveraging the power of GPUs for parallel computing tasks
refer: Wikipedia
In this GPU Programming training program, Participants will learn the basics of GPU architecture, programming models, and optimization techniques, with a focus on practical applications and hands-on exercises using CUDA..
GPU corporate training and certification oriented remote program aims to upskill you with GPU Architecture, CUDA Programming, Kernel Development, Data Parallelism, Optimization Techniques
Currently due to Covid19 outbreak, the course is available remote and however it can also be accessed online via your nearby Prog360 centre based on local availability.
Course Prerequisites
• Basic understanding of programming concepts • Familiarity with C/C++ programming language
Course Content
- Introduction to Parallel Computing and GPUs
- What is Parallel Computing?
- Overview of GPU Architecture
- Key features and benefits of GPUs
- GPU Hardware and Software Architecture
- GPU vs. CPU Architecture
- Stream Processors and Multiprocessors
- Memory Hierarchy in GPUs
- Setting Up the Development Environment
- Installing CUDA Toolkit
- Configuring the development environment
- Introduction to CUDA documentation and resources
- Setting Up CUDA Environment
- Installing and configuring CUDA Toolkit
- Exploring the CUDA development environment
- CUDA Programming Model
- Host and Device Interaction
- CUDA Execution Model
- Memory Model and Data Transfer
- Writing Your First CUDA Program
- Basic structure of a CUDA program
- Compiling and running CUDA programs
- Error handling in CUDA
- Writing Basic CUDA Programs
- Developing and running a simple CUDA program
- Implementing basic error handling
- CUDA Memory Management
- Memory objects: Global, Shared, and Local Memory
- Memory allocation and data transfer
- Optimizing memory usage
- Memory Management in CUDA
- Creating and managing memory objects
- Implementing efficient data transfer
- Introduction to CUDA Kernels
- Writing kernel functions
- Kernel arguments and execution
- Debugging kernels
- Developing CUDA Kernels
- Writing and executing simple kernels
- Debugging kernel functions
- Thread and Block Management
- Understanding Threads, Blocks, and Grids
- Synchronization and Barriers
- Managing thread divergence
- Thread and Block Management
- Implementing Threads, Blocks, and Grids in kernels
- Managing synchronization and barriers
- Optimizing CUDA Performance
- Profiling and Benchmarking
- Memory Coalescing and Alignment
- Loop Unrolling and Vectorization
- Performance Optimization
- Profiling and benchmarking CUDA programs
- Implementing optimization techniques
- CUDA Events and Streams
- Using Events for synchronization
- Stream-based execution and dependencies
- Best practices for synchronization
- Events and Streams
- Implementing event-based synchronization
- Managing execution dependencies
- CUDA Libraries and Frameworks
- Introduction to CUDA Libraries (cuBLAS, cuFFT, cuRAND)
- Using Thrust for high-level parallel programming
- Introduction to TensorFlow and PyTorch with CUDA
- Using CUDA Libraries
- Implementing high-level parallel programming with Thrust
- Integrating CUDA libraries into applications
- Case Studies and Real-World Applications
- Examining real-world GPU programming implementations
- Analyzing case studies of successful GPU projects
- Discussing lessons learned and best practices
- Developing Cross-Platform Applications with CUDA
- Writing portable CUDA code
- Testing and deploying CUDA applications
- Cross-platform optimization strategies
- Cross-Platform Development
- Writing and testing cross-platform CUDA code
- Implementing optimization strategies
- Summary and Conclusion
- Recap of key concepts and skills
- Discussion on advanced GPU programming topics
- Next steps and further learning resources
Introduction to GPU Programming
Advanced GPU Programming Techniques
Hands-On Labs: 60% of the training will involve practical exercises and case study.
Materials: Participants will receive course materials, code samples, and resources for further learning.
Certificate of Completion: Participants who attend all sessions and successfully complete the course assessments will receive a Prog360 Certificate of Completion for the Training Program.
GPU Programming with CUDA Certifications
GPU Programming with CUDA course delivery involves case studies, examples, discussions and exercises to enhance the learning experience.
At the end of the training the participants will be awarded Course Completion Certificates on GPU Programming with CUDA.
Post Course Evaluation
You may chose to enroll for a post course evaluation to analyse your knowledge metrics. The post course evaluation would cover the topics related to the training delivered over the period of the complete session, like:
- Understanding GPU Architecture
- Developing and Running CUDA Programs
- Optimizing GPU Performance
- Applying GPU Programming to Real-World Problems
- GPU Fundamentals
- Parallel Programming
- CUDA Programming
- Performance Optimization
- High-Performance Computing
GPU Programming with CUDA Corporate Training
Prog360 offers on-demand corporate learning and development solutions around GPU that can be delivered both onsite and remote (based on availability). With Prog360, you can train your employees with our 360 Approach which not only enhance professional skills but also improvise inter-personal development. Please feel free to inquire further. We are open to discuss your requirement to provide you more customized solution specific to your needs. We will evaluate the skillset, analyze the business requirement and post that provide customized training solutions as per your business needs. Our corporate team for GPU training is based across the globe hence you can reach us nearby your region as well. For general training inquiries you can contact us at training@prog360.com.
GPU Programming with CUDA Consultation
If you have already up-skilled your team and have started implementing GPU, but are still facing challenges, Prog360 can still help you. Our SMEs can get on a call with you to understand the situation and provide you a plan involving the next steps covering both audit and implementation based on your problem statement. Our corporate team for GPU consultation is based across the globe hence you can reach us nearby your region as well. For general consultation inquiries you can contact us at consult@prog360.com . For more nearby inquiries you can reach your nearby team.
South East Asia and Oceania
Oceania: Melbourne, Australia: 152 Elizabeth St,Melbourne,VIC,Melbourne,
Corporate Training: training.au@prog360.com
Consulting Services: consult.au@prog360.com
South East Asia: Singapore: 5, Temasek Boulevard, Singapore, Central Region, 03898, Singapore
Corporate Training: training.sg@prog360.com
Consulting Services: consult.sg@prog360.com
Contact Number :- +61 3 9015 4952
South Asia and Middle East
South Asia: Bengaluru, India: No. 78, Next to KR Puram Tin Factory, Old Madras Road, Bangalore – Mahadevapura, Bengaluru, Karnataka, 560016
Corporate Training: training.southasia@prog360.com
Consulting Services: consult.southasia@prog360.com
Middle East:- Dubai, UAE: The Offices 4, One Central Dubai World Trade Center, Dubai, Dubai, 00000, UAE
Corporate Training: training.ae@prog360.com
Consulting Services: consult.ae@prog360.com
Contact Number :- +91 9810 643 989