Bernat Font

The [v1.1.0](https://github.com/weymouth/WaterLily.jl/releases/tag/v1.1.0) release makes the solver fully differentiable using [ForwardDiff.jl](https://github.com/JuliaDiff/ForwardDiff.jl) on the CPU backend of [KernelAbstractions.jl](https://github.com/JuliaGPU/KernelAbstractions.jl), but is currently not working on the GPU backend.

At some point we should change the CI to use [JuliaGPU](https://github.com/JuliaGPU) servers so we can run both CPU and GPU tests on different backends.

WaterLily performance regression on CPU multi-threading backend for Julia 1.12.0

1

Here are some WaterLily benchmarks with Float32 comparing Julia 1.11.5 with 1.12.0. The KA CPU multi-threading backend shows performance regression on Julia 1.12.0, specially on CPUx04 where allocations are increasing...

Implemented 2D streamlines and vizualization routine

2

Also compatible with 3D slices.

Abstract flow and boundary conditions

4

First implementation of abstract boundary conditions (BCs), which are now called during `project!`. Needs improvements in docs and some cleanup.