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CUDA Programming Course

CUDA Programming Course
4 to 360 hours of flexible workload
certificate valid in your country

What Will I Learn?

This CUDA Programming Course equips you with practical, performance-oriented skills to design, optimise, and benchmark high-speed GPU kernels. You will 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.
Workload: between 4 and 360 hours

What our students say

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