Gpu Programming
If you like applying Gpu Programming, every challenge here gives you a chance to practice it on a real industry brief.
- CodeExpertNew
Port a CPU Monte-Carlo Simulator to GPU for an Energy Trader
Receive the existing simulator (C++17 + OpenMP, around 5,000 lines), the test book (around 8,000 spread options), and access to an H100 80GB. Port to CUDA: random-number generat…
- Gpu Programming
- Cuda
- Monte Carlo
Advanced Concurrency and Parallel Computing - CodeAdvancedNew
GPU-Parallel Graph Coloring for an EDA Tools Vendor
Implement Jones-Plassmann graph coloring in CUDA (or HIP if AMD hardware available). Input: a 12-million-node graph in CSR format (compressed sparse row). Output: a valid colori…
- Parallel Algorithms
- Gpu Programming
- Cuda
Parallel and Distributed Algorithms - CodeExpertNew
Port a Numerical Kernel from CPU to GPU for a CFD Simulator
Receive the existing CFD solver (C++17 + OpenMP, around 8,000 lines, the hot kernel is a 7-point stencil sweep over a 512^3 grid), the validation harness, and access to an A100 …
- Gpu Programming
- Cuda
- Parallelism
Performance Engineering of Software Systems - CodeAdvancedNew
Port a Monte Carlo Engine to CUDA for an Asset Manager
Profile the CPU MC engine to identify the kernel candidates: path generation (Brownian motion + correlated factors), payoff evaluation, aggregation. Port to CUDA: use cuRAND for…
- Cuda
- Monte Carlo
- Gpu Programming
High-Performance and Scientific Computing Practice your coursework on real scenarios.
Every challenge is shaped from real industry context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
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