Course Outline
Introduction
- What is GPU programming?
- Why use CUDA with Python for government applications?
- Key concepts: Threads, Blocks, Grids
Overview of CUDA Features and Architecture for Government Use
- Comparison of GPU and CPU architecture
- Understanding SIMT (Single Instruction, Multiple Threads)
- CUDA programming model
Setting up the Development Environment for Government Projects
- Installing CUDA Toolkit and drivers
- Installing Python and Numba
- Configuring and verifying the environment
Fundamentals of Parallel Programming for Government Applications
- Introduction to parallel execution
- Understanding threads and thread hierarchies
- Working with warps and synchronization mechanisms
Utilizing the Numba Compiler for Government Projects
- Introduction to Numba
- Writing CUDA kernels using Numba
- Understanding @cuda.jit decorators
Building a Custom CUDA Kernel for Government Use
- Developing and launching a basic kernel
- Using threads for element-wise operations
- Managing grid and block dimensions effectively
Memory Management in GPU Programming for Government Applications
- Types of GPU memory (global, shared, local, constant)
- Data transfer between host and device
- Optimizing memory usage to enhance performance
Advanced Topics in GPU Acceleration for Government Projects
- Shared memory and synchronization techniques
- Using streams for asynchronous execution
- Basics of multi-GPU programming
Converting CPU-based Applications to GPU for Enhanced Performance in Government
- Profiling CPU code to identify bottlenecks
- Identifying sections that can be parallelized
- Porting logic to CUDA kernels efficiently
Troubleshooting and Debugging for Government Applications
- Debugging techniques for CUDA applications
- Common errors and resolution strategies
- Tools and methodologies for testing and validation
Summary and Next Steps for Government Developers
- Review of key concepts in GPU programming
- Best practices for effective GPU programming in government
- Resources for continued learning and development
Requirements
- Python programming experience
- Experience with NumPy (ndarrays, universal functions, etc.)
Audience for government
- Developers
Testimonials (1)
Very interactive with various examples, with a good progression in complexity between the start and the end of the training.