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GPU-Parallel Graph Coloring for an EDA Tools Vendor

FreeVerified credential3 weeksAdvanced

Overview

What this challenge is about.

GPU-Parallel Graph Coloring for an EDA Tools Vendor. Advanced challenge in code. Writing production code that solves real engineering problems, earn a blockc...

CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced

The Brief

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

Reduce 12-million-node graph coloring from 90s CPU to under 10s GPU while keeping color count within 1.2x of the CPU baseline.

This is not a coding exercise. It is the work a software engineer does between a Jira ticket and a merged PR. That distinction matters to every hiring manager who has seen candidates solve LeetCode problems and none who have shipped production code under real constraints.

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

  • Reason about GPU memory hierarchy and coalesced access for graph workloads
  • Implement a parallel graph algorithm that respects independence constraints
  • Benchmark GPU kernels honestly (kernel time, transfer time, end-to-end)
  • Recommend shipping decisions that respect where the new approach degrades

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Parallel and Distributed Algorithms

Master · Algorithms

Strong alignment

This challenge maps to Parallel and Distributed Algorithms at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.

One more thing

You can put a credential on your CV by Friday.

GPU-Parallel Graph Coloring for an EDA Tools Vendor