CUDA Course
This course provides hands-on training in CUDA programming, focusing on stencil kernels, shared memory optimisation, and GPU architecture tuning. Participants learn to adapt 2D computational problems to GPU frameworks, enhance memory access patterns and thread utilisation, and evaluate performance metrics on actual workloads to achieve substantial speed improvements in production environments.

flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
Gain expertise in GPU acceleration through this comprehensive CUDA course, progressing from basic CPU implementations to highly optimised 2D stencil kernels. Explore the CUDA programming model, warps, occupancy, and synchronisation techniques, then develop efficient kernels using shared memory tiling, halo management, and optimal block configurations. Master profiling, benchmarking, correctness validation, and architecture-specific optimisations for high-performance real-world applications.
Elevify advantages
Develop skills
- Design efficient CUDA kernels by mapping 2D grids to optimal blocks and threads.
- Optimise GPU memory usage with shared memory tiling, coalesced accesses, and bank conflict resolution.
- Fine-tune kernels for NVIDIA GPUs through profiling, improving occupancy, and eliminating bottlenecks.
- Develop reliable 2D stencil implementations handling boundaries, selecting precision, and rigorous testing.
- Compare CPU and GPU performance by measuring speedups, GFLOPS, and memory bandwidth improvements.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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