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CUDA Programming Course

CUDA Programming Course
from 4 to 360h flexible workload
valid certificate in your country

What will I learn?

This CUDA Programming Course equips you with practical, performance-driven skills to design, optimise, and benchmark high-speed GPU kernels. You will explore GPU architecture, memory hierarchy, warps, and synchronisation, then implement coalesced access, shared memory, streams, and vectorised loads in real numeric tasks. Conclude with profiling, multi-GPU scaling, and a production-ready checklist for reliable, reproducible outcomes.

Elevify advantages

Develop skills

  • Optimise CUDA kernels: adjust blocks, streams, and memory for efficient numeric code.
  • Master GPU memory: handle shared, global, caches, and coalesced access patterns.
  • Profile CUDA applications: utilise Nsight tools to identify and resolve performance issues.
  • Design solid experiments: benchmark kernels, assess speedup, and report findings clearly.
  • Scale GPU workloads: employ multi-GPU, unified memory, and kernel fusion strategies.

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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