particle attributes through consideration of neighboring particles within a finite set. Among the forefront concerns in SPH methodologies is the replication of incompressible fluid behavior, a challenge met by SPlisHSPlasH through the integration of cutting-edge pressure solvers (WCSPH, PCISPH, PBF, IISPH, DFSPH, PF). Furthermore, the toolkit offers diverse strategies for simulating viscosity, surface tension, and vorticity, enhancing its versatility in fluid simulations. The code incorporates various external libraries, including Eigen, json, partio, zlib, cxxopts, tinyexpr, toojpeg, pybind, glfw, hapPLY, nfd, and imgui. These dependencies are all bundled within the package. Additionally, code utilizes custom libraries such as: (1) PositionBasedDynamics for dynamic rigid body simulation, (2) Discregrid for collision detection among rigid bodies, (3) CompactNSearch for neighborhood search functionality,(4) cuNSearch for GPU-accelerated neighborhood search, (5) GenericParameters for managing generic parameters. SPlisHSPlasH offers the capability to export particle data in both partio and vtk formats. To seamlessly import partio files into Maya or Blender, consider utilizing our plugins: Blender Sequence Loader: https://github.com/InteractiveComputerGraphics/blender-sequence-loader . MayaPartioTools: https://github.com/InteractiveComputerGraphics/MayaPartioTools . Author of this work is Jan Bender (https://animation.rwth-aachen.de/person/1/). The SPlisHSPlasH library code is licensed under the MIT license (https://github.com/InteractiveComputerGraphics/SPlisHSPlasH/blob/master/LICENSE). External dependencies are covered by separate licensing terms. See the extern folder for the code and respective licensing terms of each dependency. Image/animation source: https://raw.githubusercontent.com/InteractiveComputerGraphics/SPlisHSPlasH/master/doc/images/teaser.gif