CUDA Programming Course
This course equips learners with essential CUDA programming skills for high-performance GPU computing, covering kernel optimization, memory management, profiling, benchmarking, and scaling techniques for numeric workloads.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This CUDA Programming Course provides practical, performance-focused skills to design, optimise, and benchmark high-speed GPU kernels. You'll learn GPU architecture, memory hierarchy, warps, and synchronisation, then apply coalesced access, shared memory, streams, and vectorised loads to real numeric workloads. Finish with profiling, multi-GPU scaling, and a production-ready checklist for robust, reproducible results.
Elevify advantages
Develop skills
- Optimise CUDA kernels: tune blocks, streams, and memory for fast numeric code.
- Master GPU memory: shared, global, caches, and coalesced access patterns.
- Profile CUDA apps: use Nsight tools to find and fix real performance bottlenecks.
- Design robust experiments: benchmark kernels, measure speedup, and report clearly.
- Scale GPU workloads: apply 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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