Build a Performance Model for a Molecular-Dynamics Job
Overview
What this challenge is about.
Calibrate a performance model for a molecular-dynamics job and build a CLI tool to recommend rank counts. Deliver source code and a verifiable certificate.
The scenario
The pharma group (publicly listed, multi-billion EUR R&D budget) wastes an estimated CHF 280k/year of cluster allocation to oversized or undersized MD jobs.
The Brief
What you'll do, and what you'll demonstrate.
Build a calibrated analytical performance model for GROMACS MD runs and a CLI tool that recommends optimal rank + node count for a given simulation.
Earning criteria — what you'll demonstrate
- Derive an analytical performance model from first principles
- Design a controlled benchmark sweep that supports model calibration
- Validate model predictions against held-out experimental runs
- Translate a performance model into an end-user CLI tool
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Performance Modeling
Apply performance modeling to solve real industry problems and demonstrate production-level capability.
- Gromacs
Apply gromacs to solve real industry problems and demonstrate production-level capability.
- Benchmark Design
Apply benchmark design to solve real industry problems and demonstrate production-level capability.
- Python Programming
Apply python programming to solve real industry problems and demonstrate production-level capability.
- Calibration
Apply calibration to solve real industry problems and demonstrate production-level capability.
- Hpc Job Sizing
Apply hpc job sizing to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles: