CUDA Course
4.7/5
Dive into CUDA programming with practical 2D stencil kernels, shared memory strategies, and hardware-tuned optimisations. Master mapping 2D challenges to GPU architectures, refining memory usage and thread management, while benchmarking actual workloads to deliver substantial performance boosts in operational environments. This course equips you to harness NVIDIA GPUs for superior computational efficiency in production applications.

4.7 in the evaluation
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain expertise in GPU acceleration through this targeted CUDA course, progressing from CPU fundamentals to high-performance 2D stencil kernels. Explore CUDA programming model, warps, occupancy, and synchronisation techniques, then craft efficient kernels using shared memory tiling, halo management, and optimised block configurations. Profile, benchmark, verify accuracy, and implement architecture-specific optimisations for demanding, real-world high-performance tasks.
Elevify advantages
Develop skills
- Design efficient CUDA kernels by mapping 2D grids to optimal blocks and threads.
- Optimise GPU memory patterns with shared tiling, coalesced accesses, and bank conflict resolutions.
- Fine-tune kernels for NVIDIA GPUs through profiling, maximising occupancy, and eliminating bottlenecks.
- Build reliable 2D stencil implementations handling boundaries, precision, and rigorous testing.
- Benchmark CPU against GPU performance, quantifying speedups, GFLOPS, and bandwidth improvements.
Suggested summary
Before starting, you can change the chapters and 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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