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Cache-Optimize a Graph-Analytics Kernel for a Social Platform

FreeVerified credential4 weeksExpert

Overview

What this challenge is about.

Cache-Optimize a Graph-Analytics Kernel for a Social Platform. Expert-level challenge in code. Writing production code that solves real engineering problems,...

CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced

The Brief

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

Re-design a friend-of-friend graph kernel for cache locality (reordering + blocking + prefetching) and prove 6-10x speedup with result equivalence.

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

  • Distinguish bandwidth-bound vs. latency-bound kernels with perf + likwid
  • Apply vertex reordering (Gorder, RCM) to graph workloads
  • Tune cache-blocking and software prefetching for a real CPU
  • Validate optimization equivalence honestly on sampled queries

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Performance Engineering of Software Systems

Master · Systems

Strong alignment

This challenge maps to Performance Engineering of Software Systems 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.

Cache-Optimize a Graph-Analytics Kernel for a Social Platform