Open-source alternatives to FluidX3D

This project is a parallel simulation engine and molecular dynamics simulator designed to model the physical movements of atoms and molecules. It functions as an interatomic potential framework for calculating forces between particles and a materials analysis tool for computing thermodynamic, structural, and transport properties of solids and fluids. The engine is distinguished by its high-performance computing capabilities, utilizing spatial-domain decomposition and message-passing interface communication to distribute workloads across processors. It supports multi-backend GPU acceleration v

Mixbox is a specialized simulation engine for modeling fluid color dynamics, pigment-based hue shifts, and latent space color blending. It functions as an RGB color mixing simulator that uses pigment-based simulations and latent space interpolation to produce realistic results. The project incorporates a Kubelka Munk color engine to achieve physically accurate hue shifts and saturated gradients. It also utilizes a latent space color blender to transform colors into latent representations for precise linear interpolation and multi-color mixing. The system covers fluid dynamics for calculating

The compute runtime is a software layer that provides unified interfaces for parallel processing, kernel execution, and hardware-specific driver communication. It functions as a driver for OpenCL and OneAPI Level Zero, enabling the execution of data-intensive workloads across diverse graphics hardware architectures. The project distinguishes itself by maintaining consistent performance and compatibility across multiple generations of graphics hardware. It achieves this through a hardware abstraction layer that bridges high-level compute instructions with specific silicon capabilities, alongsi

Newton is a GPU-accelerated physics engine and robotics simulation platform designed for high-performance modeling of rigid bodies and complex articulations. It functions as a differentiable physics engine, calculating gradients to enable mathematical optimization and machine learning. The platform is distinguished by its ability to execute multiple parallel physics worlds on a single GPU, which accelerates data collection for reinforcement learning. It also supports the simulation of deformable bodies, such as cloth and cables, using particle-based methods and multi-physics coupling. Newton

IsaacGymEnvs is a GPU-accelerated physics sandbox and robotics policy training suite designed for reinforcement learning. It serves as a vectorized robotic simulator that runs thousands of parallel environments on GPUs to accelerate the training of neural networks. The project provides a sim-to-real transfer framework that utilizes domain randomization and physics variations to ensure policies trained in simulation are robust enough for deployment on real hardware. It distinguishes itself through a high-performance architecture that uses tensor-based state management to handle observations an

Orillusion is a WebGPU 3D rendering engine designed for high-fidelity scenes and visual effects in the browser. It functions as a GPU compute framework for parallel mathematical operations and a physically-based rendering graphics pipeline for realistic materials and surfaces. The system also includes a web-based 3D animation toolkit for driving skeletal animations and interpolating vertex positions. The engine is distinguished by its use of an entity component system for scene logic and a macro-based shader generation system that creates multiple shader variants. It optimizes performance thr

Evolve is an evolution-based organism designer and GPU-accelerated artificial life simulator that combines interactive particle physics with a real-time simulation editor. At its core, it runs genetic algorithm evolution on self-replicating graph structures to evolve digital organisms, offloading particle physics, neural networks, and rendering entirely to the GPU through a compute shader pipeline for real-time performance. The project distinguishes itself with graph-based organism design that uses a directed graph editor to visually define organism structure, connections, and neural controll

This project is a GPU-accelerated fluid renderer and interactive WebGL visualizer. It functions as a fluid dynamics sandbox for experimenting with the real-time movement and behavior of liquids. The simulation calculates density, pressure, and vorticity using GPU shaders to maintain high performance. It includes atmospheric visual effects such as bloom and sunrays, alongside tools for capturing the simulation state as static images. The underlying architecture utilizes fragment-shader rendering and ping-pong texture buffering to manage fluid physics. Multi-pass post-processing is used to app

This project is a cross-platform graphics wrapper and translation layer that implements the OpenGL ES and EGL specifications. It functions as a graphics API bridge, mapping OpenGL ES calls and WebGL content to platform-specific hardware APIs such as Vulkan and Metal to ensure consistent rendering across different operating systems. The system features a shader translation service that validates shading language code and transpiles it into multiple target languages, including HLSL, SPIR-V, and Metal SL. It employs a pluggable backend architecture to select the appropriate hardware rendering AP

LiquidFun is a 2D physics engine and game physics framework designed to calculate movement and collisions for rigid bodies and particle systems. It functions as a simulation tool for integrating real-time physical interactions and dynamics into interactive applications. The framework specifically provides a particle-based fluid simulator to model liquid dynamics, including splashing, displacement, and surface tension. It also includes a soft body physics simulator for creating deformable and elastic objects that react to physical forces. The engine covers a broad range of physical interactio

Hashcat is a high-performance hash cracking software and OpenCL compute application used to recover plain-text passwords from hashed data. It functions as a GPU-accelerated recovery tool and distributed password cracker, leveraging CPUs and GPUs to perform intensive cryptographic computations. The system differentiates itself through a distributed cracking workflow that coordinates tasks across multiple machines via an overlay network to share computational load. It further optimizes recovery speed using Markov chain keyspace optimization to prioritize the most likely password candidates. Th

CFDPython is an educational resource for computational fluid dynamics and numerical analysis. It provides a structured curriculum to learn the physics of fluid flow by implementing numerical solutions to Navier-Stokes and partial differential equations. The project is organized as a series of incremental coding exercises delivered via Jupyter notebooks. Users build mathematical models for linear convection, diffusion, and Poisson equations across one and two dimensions to understand concepts such as convergence, stability, and numerical diffusion. The implementation utilizes NumPy for vector

XMRig is a multi-algorithm hashing tool and cryptocurrency miner that utilizes CPU, CUDA, and OpenCL hardware to execute hashing algorithms across multiple operating systems. It functions as a computational engine for mining cryptocurrency and benchmarking hardware efficiency. The project includes a Stratum proxy server that routes mining traffic between worker clients and pools to optimize connectivity and balance load. It also provides a secured HTTP management API for monitoring hashrates and modifying miner configuration in real time without restarting the process. The software covers a

Chrono is a multi-physics simulation suite that functions as a multibody dynamics simulator, a finite element analysis tool, and a robotics simulation framework. It provides specialized solvers for fluid-solid interaction and distributed physics engines capable of synchronizing multiple agents across a network. The project features a dedicated pipeline for converting CAD assemblies into simulation-ready formats and integrates directly with robot operating systems to validate autonomous control logic and sensors. It differentiates itself through the use of WebAssembly for portable browser-base

This library is a web-based framework designed for general-purpose parallel processing and high-performance computation on graphics hardware. It provides a toolkit for executing complex mathematical operations, physics simulations, and procedural visualizations directly within the browser by leveraging the graphics processor for data-intensive tasks. The framework distinguishes itself through automated shader management, which ensures consistent execution across diverse hardware and browser environments. It achieves this by transpiling modern shader syntax into legacy versions and automatical

LWJGL is a cross-platform library that provides Java bindings to native APIs for graphics, audio, compute, windowing, and input. It enables Java applications to access low-level hardware-accelerated capabilities such as OpenGL and Vulkan rendering, OpenAL 3D audio, OpenCL GPU compute, and GLFW windowing and input handling. Under the hood, LWJGL dynamically resolves native function pointers at runtime, loads platform-specific shared libraries, and uses generated JNI bindings to bridge Java and native code. It offers explicit memory management through direct buffer access and stack-allocated me

DeepXDE is a scientific machine learning library and deep learning PDE solver used to compute solutions for forward and inverse ordinary, partial, and integro-differential equations. It functions as a physics-informed neural network library that embeds physical laws and boundary conditions directly into the neural network loss function. The project provides a deep operator network framework for learning operator mappings that approximate relationships between functions in multiphysics problems. It is implemented as a multi-backend tensor library, allowing the system to switch between differen

pifuhd is a 3D human reconstruction framework that generates high-resolution 3D meshes of people from a single 2D image. It utilizes pixel-aligned implicit functions to map image pixels to 3D space, predicting surface occupancy and distance to create detailed geometry. The system includes a pipeline for creating digital human assets, moving from 2D image feature projection to the extraction of discrete triangular meshes. It features specialized tools for refining these models, including a post-processor that removes geometric artifacts by isolating the largest connected component of the mesh.

libigl is a C++ geometry processing library used for analyzing and manipulating 3D triangle and tetrahedral meshes. It functions as a numerical linear algebra suite and a mesh manipulation framework, integrating a geometric deformation engine to implement rigid and polyharmonic transformations. The project is distinguished by its header-only library design and its implementation of specialized deformation techniques, including rigid-as-possible and polyharmonic shape deformation. It also provides a visualization tool for rendering surfaces and scalar fields with interactive scene controls and

Neuralangelo is a neural surface reconstruction framework that transforms two-dimensional image sequences and multi-view photography into high-fidelity 3D meshes. It implements a pipeline for training neural radiance fields to represent complex scenes as digital geometry. The project utilizes a signed distance function for surface representation and multi-resolution hash encoding to capture both coarse and fine geometric details. It employs differentiable volume rendering and gradient-based eikonal regularization to ensure the learned distance functions remain physically plausible. The syste

Wonder3D is a diffusion-based system for single image 3D reconstruction. It generates high-detail 3D meshes from a single input image by producing consistent multi-view normal maps and color images. The pipeline functions as a multi-view normal map generator and a textured mesh extractor. It uses cross-domain multi-view synthesis to create view-dependent maps, which are then converted into 3D geometry through radiance fusion and memory-efficient surface reconstruction. The project covers 3D mesh generation, multi-view generation, and textured 3D modeling. It also includes capabilities for tr

ComfyUI-3D-Pack is a suite of custom nodes for ComfyUI that enables 3D asset generation and rendering within a node-based workflow. It provides a set of tools for reconstructing textured three-dimensional meshes and volumetric scenes from single images, multi-view images, or text prompts. The system includes a Gaussian splatting generator for creating high-fidelity volumetric 3D scene representations and a multi-view image generator to produce consistent image sets for reconstruction. It also features a single image 3D mesh tool to build geometry from a single 2D source. The toolset covers 3

This project is a framework for neural radiance fields used to synthesize three-dimensional environments from sets of two-dimensional images and camera poses. It functions as a volumetric rendering engine and scene synthesizer that optimizes neural representations of spatial volumes to generate novel views of complex 3D scenes. The system implements a coordinate encoding system that transforms spatial coordinates into high-dimensional space to capture high-frequency geometric details. It also includes a neural mesh extractor that converts trained radiance fields into triangle meshes via march

Instant Meshes is a 3D surface remesher and computational geometry tool designed to generate optimized polygonal grids over existing three-dimensional models. It functions as a field-aligned mesh generator that computes orientation and position fields to ensure the resulting mesh follows the geometric flow and contours of a target surface. The tool distinguishes itself through an interactive mesh editor that allows for the manual refinement of these mathematical fields. Users can employ brush tools to adjust orientation and position fields, steering the mesh topology in real time through iter

vrn is a 3D face reconstruction tool that generates three-dimensional volumetric representations of human faces from single two-dimensional images. It utilizes a volumetric convolutional neural network regression model to predict 3D volume data directly from image pixels. The system converts these volumetric predictions into 3D meshes through isosurface extraction and vertex coloring. It further applies realistic surface details by mapping two-dimensional image pixels onto the resulting 3D mesh using nearest-neighbor texture projection. The project provides capabilities for single-image dept

This project is a diffusion-based 3D generator and image-to-3D reconstruction system. It translates natural language descriptions or two-dimensional images into three-dimensional assets using neural radiance fields and diffusion models. The system utilizes score-distillation sampling and diffusion-based guidance to refine 3D shapes without requiring 3D training data. It includes specialized tools for transforming neural representations into exportable meshes with texture and material data, as well as a pipeline for iterative optimization of geometry and textures. The project covers a broad r