PacktPublishing/Learn-CUDA-Programming resource

Health v2 · maintenance only

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1261 stars · 260 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

The companion code repository for the Packt book 'Learn CUDA Programming', a beginner's guide to GPU programming and parallel computing with CUDA 10.x and C/C++. It contains chapter-by-chapter example code covering GPU operations, performance optimization, profiling, multi-GPU scaling, and deep learning acceleration.

Use cases

• learn CUDA GPU programming from scratch
• study parallel computing examples in C/C++
• optimize GPU application performance
• profile and debug CUDA applications
• scale workloads across multiple GPUs and nodes
• accelerate deep learning models with GPUs
• practice GPU programming with Python interop and OpenACC

When to choose

• you are following the Packt book and want runnable code for each chapter
• you are a C/C++ programmer new to GPU and parallel computing
• you want hands-on examples of CUDA profiling, optimization, and multi-GPU scaling
• you are a deep learning practitioner wanting GPU performance insights

When to avoid

• you need a production CUDA library or framework rather than educational code
• you want a maintained, actively updated CUDA tutorial (code targets CUDA 10.x)
• you have no C/C++ background and need a gentler introduction
• you need CUDA examples for recent GPU architectures or newer CUDA versions

Facets

learning-resource · maturity maintenance

gpu-computing machine-learning developer-tools gpu-computing tutorials machine-learning developer-tools cpp python windows cuda book-code packt parallel-computing high-performance-computing gpu-programming openacc profiling gpu linux macos

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