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Analysis

GPU Roofline Model Study for a Computer Vision Inference Workload

FreeVerified credential3 weeksAdvanced

Overview

What this challenge is about.

GPU Roofline Model Study for a Computer Vision Inference Workload. Advanced challenge in analysis. Analyzing real datasets and building models that drive dec...

CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced

The Brief

What you'll do, and what you'll demonstrate.

Build empirical roofline models for two GPU generations, profile a ResNet-50 inference workload, and recommend batch-size-and-SKU placement.

This is not a data exercise. It is the work an analyst does when stakeholders need answers from messy data. That distinction matters to every hiring manager who has seen candidates describe statistical methods and none who have extracted insight from messy, real-world data.

When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."

Earning criteria — what you'll demonstrate

  • Construct an empirical roofline model from measured peak FLOPs and bandwidth
  • Profile a real GPU workload with Nsight Compute
  • Map workload regimes to GPU SKUs based on arithmetic intensity
  • Communicate placement recommendations to a capacity team

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Aligned coursework coming soon.

One more thing

You can put a credential on your CV by Friday.