Intermediate Learning Path

Build on your foundational knowledge to create efficient, production-quality GPU applications.

Prerequisites

• Completed Beginner Path or equivalent experience
• Understanding of GPU threads, blocks, and memory spaces
• Experience writing basic kernels

Learning Objectives

By completing this path, you will:

1. Optimize memory allocation and transfer patterns
2. Tune kernel performance through thread configuration
3. Build multi-kernel processing pipelines
4. Implement robust error handling and debugging

Modules

Module 1: Memory Optimization

Duration: 60-90 minutes

Master memory pooling, allocation strategies, and transfer optimization.

Start Module 1 →

Module 2: Kernel Performance

Duration: 60-90 minutes

Optimize thread configuration, occupancy, and use profiling tools.

Start Module 2 →

Module 3: Multi-Kernel Pipelines

Duration: 60-90 minutes

Chain kernels efficiently and manage complex data flows.

Start Module 3 →

Module 4: Error Handling

Duration: 45-60 minutes

Debug GPU code and handle failures gracefully in production.

Start Module 4 →

Completion Checklist

• [ ] Configure memory pooling for allocation efficiency
• [ ] Profile and optimize kernel occupancy
• [ ] Build a multi-stage processing pipeline
• [ ] Implement comprehensive error handling
• [ ] Debug GPU kernel issues effectively

Next Steps

After completing this path, continue to the Advanced Path to learn about Ring Kernels, synchronization, and multi-GPU programming.

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Estimated total duration: 4-6 hours