Welcome to the SU2 Google Summer of Code Page

Welcome to SU2 - GSOC!

This is the updated ideas list for GSOC 2026.

Project BP: Adding pressure-based solver

Project Description (max. 5 Sentences) The pressure-based solver has been requested for a long time. This solver is an important addition to the CFD solvers, especially for low Mach and incompressible flows. People have worked on it (detailed documentation available), and there is a branch that contains a working version, but this was never finalized and added to the main SU2 branch. Hence, the project’s objective is to evaluate the current status of attempts, and propose a strategy for getting the pressure-based solver in the latest version of SU2. Expected Outcome (deliverables): Finalize pressure-based solver, validate with test cases, tutorial and merge the PR.

  • Skills Required: C++, experience with CFD and numerical methods
  • Possible Mentors: Nitish Anand and Edwin van der Weide
  • Expected Project Size: 175 hrs/medium
  • Difficulty rating: medium-hard (needs experience with Computational Fluid Dynamics)

Project GPU: Continuation of GPU acceleration in SU2

Project Description (max. 5 Sentences) The SU2 code relies heavily on sparse linear algebra. In this area, there is significant speed-up potential with the adoption of GPU-based processing, as was demonstrated in the GSOC 24 project that applied CUDA to sparse matrix-vector multiplications in SU2. The objective of this project is to move more linear algebra operations to GPU in order to avoid host-device communication bottlenecks within the sparse linear system solver. Expected Outcome (deliverables): Make SU2’s sparse linear solver GPU-native, i.e. minimal host-device communication after the initial setup of the system.

  • Skills Required C++
  • Possible Mentors Pedro Gomes (lead), Ole Burghardt
  • Expected Project Size (90 hrs/ small , 175 hrs/medium, 350 hrs/large): 175 hrs (medium)
  • Difficulty rating: medium

Project AMR: Quick Adaptive Mesh refinement for 2D testcases

Project Description (max. 5 Sentences) Many users have asked for adaptive mesh refinement capabilities. Several research groups are working on this. The aim of this project is to introduce a quick and easy adaptive mesh refinement that simply reads an existing results file and adaptively refines the meshes based on the value of a field. Expected Outcome (deliverables): SU2_AMR, an added executable that simply splits 2D quad and triangle cells

  • Skills Required: C++
  • Possible Mentors: Nijso Beishuizen (lead)
  • Expected Project Size (90 hrs/ small , 175 hrs/medium, 350 hrs/large): 175 hrs (medium)
  • Difficulty rating: medium


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