GSoC 2022 Project Idea 1.1: Improving GPU-accelerated Monte Carlo simulations in Disimpy: Adding new features (175/350 h)

Disimpy is a GPU-accelerated diffusion-weighted magnetic resonance simulator that is useful in the development and validation of neuroimaging methods. Disimpy is written in Python, making the source code very approachable to researchers with little or no prior experience in GPU-computing.

Project: Adding new features such as new substrates (e.g., analytical geometries or triangular meshes) or new dynamics (e.g., permeability or flow). Skill level: Novice to advanced.

Required skills: Python, NumPy.

Nice-to-have skills: 3D modelling for advanced projects.

Time commitment: half-time or full-time.

Lead mentor: Leevi Kerkelä @kerkelae

Backup mentors: Rafael Neto Henriques, Marco Palombo

Project website:

Tech keywords: Python, NumPy, Numba, CUDA, 3D modelling

Hi! I’m really interested to work on this project and would love to learn more about it :slight_smile:

Great to hear that! I sent you a message so we can organize a meeting to discuss.

Hi! I would be interested to learn more about this project!