CUDA Programming Course
4/5
Master CUDA programming to create high-performance GPU kernels. Gain skills in memory hierarchy, streams, profiling, and optimisation techniques to enhance numeric workloads, speed up data transformations, and deliver faster, scalable production-ready code. This course equips you with practical knowledge for designing, optimising, and benchmarking GPU applications effectively.

4.0 in rating
flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
This CUDA Programming Course provides practical skills to design, optimise, and benchmark high-speed GPU kernels. Learn GPU architecture, memory hierarchy, warps, and synchronisation, then implement coalesced access, shared memory, streams, and vectorised loads for numeric workloads. Conclude with profiling, multi-GPU scaling, and a checklist for reliable results.
Elevify advantages
Develop skills
- Optimise CUDA kernels by tuning blocks, streams, and memory for fast numeric code.
- Master GPU memory including shared, global, caches, and coalesced access patterns.
- Profile CUDA apps using Nsight tools to identify and fix performance bottlenecks.
- Design robust experiments by benchmarking kernels, measuring speedup, and reporting clearly.
- Scale GPU workloads with multi-GPU, unified memory, and kernel fusion tactics.
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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