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Cuda Programming Course

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

What Will I Learn?

This CUDA Programming Course gives you practical, performance-focused skills to design, optimize, and benchmark high-speed GPU kernels. You will learn GPU architecture, memory hierarchy, warps, and synchronization, then apply coalesced access, shared memory, streams, and vectorized loads to real numeric workloads. Finish with profiling, multi-GPU scaling, and a production-ready checklist for robust, reproducible results.

Elevify Differentials

Develop Skills

  • Optimize 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 workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.
Workload: between 4 and 360 hours

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