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Port a CPU Monte-Carlo Simulator to GPU for an Energy Trader

FreeVerified credential4 weeksExpert

Overview

What this challenge is about.

Port a CPU Monte-Carlo Simulator to GPU for an Energy Trader. 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.

Port a Monte-Carlo simulator to CUDA, hit >=70 percent peak FP32 throughput on an H100, and validate PnL + Greeks within 1e-4 vs. 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

  • Port Monte-Carlo kernels to CUDA with warp-level reductions
  • Tune occupancy and register usage on an H100
  • Validate financial-math equivalence with Greeks, not just PnL
  • Package CUDA workloads for deployment to a shared GPU cluster

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Advanced Concurrency and Parallel Computing

Master · Systems

Strong alignment

This challenge maps to Advanced Concurrency and Parallel Computing 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.