GPU-Accelerated Numerical Optimization for Portfolio Construction
Overview
What this challenge is about.
Build a CUDA interior-point solver for 4,200-asset portfolios, benchmark against CPU solvers, and earn your verifiable certificate.
The scenario
The asset manager (around USD 180M revenue, regulated under SEC) has a rebalancing window of 45 minutes between close and post-close confirmations — a 38-minute solve consumes the entire safety margin.
The Brief
What you'll do, and what you'll demonstrate.
Cut daily portfolio-construction QP solve time from 38 minutes to under 5 minutes using GPU-accelerated interior-point methods without sacrificing KKT accuracy.
Earning criteria — what you'll demonstrate
- Implement a primal-dual interior-point method for constrained QP
- Use cuSPARSE and cuSOLVER for the dominant sparse-linear-algebra kernels
- Benchmark GPU vs CPU solvers fairly with identical accuracy targets
- Reason about the GPU vs CPU cost trade for daily production workloads
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Scientific Computing and Numerical Methods
Master · General Studies
Strong alignment
This challenge maps to Scientific Computing and Numerical Methods at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Numerical Optimization
Apply numerical optimization to solve real industry problems and demonstrate production-level capability.
- Interior Point Method
Apply interior point method to solve real industry problems and demonstrate production-level capability.
- Cuda
Apply cuda to solve real industry problems and demonstrate production-level capability.
- Gpu Computing
Apply gpu computing to solve real industry problems and demonstrate production-level capability.
- Sparse Linear Algebra
Apply sparse linear algebra to solve real industry problems and demonstrate production-level capability.
- Quadratic Programming
Apply quadratic programming 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: