mhtirogla
Home
Systems
API
Pricing
About
Log in
← Back
Home
›
Systems
›
Simulation and scientific computing
realtime-cloth-fluid
real-time cloth and fluid
PBD, FLIP
System
Techniques · 13
Primitives · 24
realtime-cloth-fluid
Marching cubes
graphics · medium: Extract triangle meshes from scalar fields (marching cubes, dual contouring)
Graph coloring
graphs · medium: Greedy/DSatur colouring for conflict-free assignment such as radio channels
Level set methods
numerics · medium: Implicit surfaces as signed distance fields: advection, reinitialization, fast marching
Continuous collision detection
physics · medium: Time-of-impact via conservative advancement or swept shapes to stop tunneling
Flip pic fluid
physics · medium: FLIP/PIC/APIC hybrid particle-grid fluid: particle-to-grid transfer, pressure solve, grid-to-particle
Position based dynamics
physics · medium: PBD and XPBD: project positions onto constraints with compliance for stable cloth and soft bodies
Pressure projection method
physics · medium: Chorin projection: solve a pressure Poisson equation to make velocity divergence-free (MAC grid, SIMPLE, PISO)
Spatial hashing
physics · low: Uniform grid stored in a hash table: bucket objects by cell, test only neighbouring cells; O(n) neighbour search for many similar-sized objects such as particles.
›
Bounding volume hierarchy
physics · low: Binary tree of nested bounding boxes; prunes overlap and ray queries to O(log n) for any size distribution, and supports cheap insert/remove for moving objects.
›
Semi-implicit Euler
numerics · low: Update velocity from forces first, then position with the new velocity: explicit Euler cost, but symplectic and stable; the default game-physics integrator.
›
Conjugate gradient
numerics · low: Krylov iteration for symmetric positive definite Ax = b using one matrix-vector product and two dot products per step; converges in about √κ iterations.
›
Multigrid
numerics · low: Smooths high-frequency error on the fine grid and solves the smooth remainder on coarser grids; O(n) elliptic solves at any resolution.
›
Radix sort
search-sort · low: Non-comparison sort that distributes keys by 8-bit digits; several times faster than comparison sorts on large arrays of integers, floats or fixed-size keys.
›
Parallel prefix sum
search-sort · low: Work-efficient scan (Blelloch, decoupled look-back) on CPU SIMD and GPUs; stream compaction
Finite differences
numerics · low: Replace derivatives with weighted differences of grid values; simple stencils plus a stability condition (CFL) turn PDEs like heat, advection and waves into array loops.
›
d-ary heap
data-structures · low: Array heap with d children per node (d = 4 typical): half the binary heap's depth, siblings in one cache line, faster priority queues.
›
BFS and DFS
graphs · low: The two basic graph traversals; BFS gives hop distances and levels, DFS gives discovery/finish order for cycles, components and topological order.
›
Runge-Kutta 4
numerics · low: The classic four-stage, fourth-order ODE step; error drops 16× when the step halves, with no derivatives or past steps needed.
›
Newton root finding
numerics · low: Linearize at the guess and jump to the tangent root; quadratic convergence near a simple root, made robust by brackets (1D) or line search.
›
GJK and EPA
physics · low: GJK decides whether (and how far apart) two convex shapes are from their support functions alone; EPA expands its simplex into penetration depth and normal.
›
Sweep and prune
physics · low: Sort box endpoints along an axis and sweep: only intervals that overlap on that axis are tested; near-linear per frame thanks to temporal coherence.
›
PRNGs (PCG, xoshiro)
numerics · low: Small, fast, statistically strong non-cryptographic generators: PCG32 and xoshiro256**, with seeding, parallel streams and unbiased ranges.
›
Spline interpolation
numerics · low: Linear, bilinear/trilinear and cubic spline interpolation on grids and tables
+ 6 more techniques
+ 8 more primitives
System
Techniques · 13
Primitives · 24
realtime-cloth-fluid
Marching cubes
graphics · medium: Extract triangle meshes from scalar fields (marching cubes, dual contouring)
Graph coloring
graphs · medium: Greedy/DSatur colouring for conflict-free assignment such as radio channels
Level set methods
numerics · medium: Implicit surfaces as signed distance fields: advection, reinitialization, fast marching
Continuous collision detection
physics · medium: Time-of-impact via conservative advancement or swept shapes to stop tunneling
Flip pic fluid
physics · medium: FLIP/PIC/APIC hybrid particle-grid fluid: particle-to-grid transfer, pressure solve, grid-to-particle
Position based dynamics
physics · medium: PBD and XPBD: project positions onto constraints with compliance for stable cloth and soft bodies
Pressure projection method
physics · medium: Chorin projection: solve a pressure Poisson equation to make velocity divergence-free (MAC grid, SIMPLE, PISO)
Semi lagrangian advection
physics · medium: Trace characteristics back and interpolate; unconditionally stable large time steps
Smoothed particle hydrodynamics
physics · medium: SPH kernels for density, pressure and viscosity on particles; neighbor search
Flux limiters upwinding
numerics · medium: Upwind schemes, TVD flux limiters, MUSCL and Riemann solvers for shock-capturing advection
Incomplete factorization preconditi…
numerics · medium: Sparse approximate LU or Cholesky factors (ILU, IC) that precondition Krylov solvers: fewer iterations than Jacobi, less memory than a direct solve.
›
Fill-reducing ordering
numerics · medium: Permute a sparse symmetric matrix before Cholesky/LU so the factor has few new nonzeros; minimum degree, nested dissection and RCM trade quality, speed and parallelism.
›
Graph partitioning
graphs · medium: Split a graph into k balanced parts with few edges between them; multilevel coarsen-partition-refine (METIS, KaHIP) for quality, streaming heuristics (LDG, Fennel) for one-pass scale.
›
Spatial hashing
physics · low: Uniform grid stored in a hash table: bucket objects by cell, test only neighbouring cells; O(n) neighbour search for many similar-sized objects such as particles.
›
Bounding volume hierarchy
physics · low: Binary tree of nested bounding boxes; prunes overlap and ray queries to O(log n) for any size distribution, and supports cheap insert/remove for moving objects.
›
Semi-implicit Euler
numerics · low: Update velocity from forces first, then position with the new velocity: explicit Euler cost, but symplectic and stable; the default game-physics integrator.
›
Conjugate gradient
numerics · low: Krylov iteration for symmetric positive definite Ax = b using one matrix-vector product and two dot products per step; converges in about √κ iterations.
›
Multigrid
numerics · low: Smooths high-frequency error on the fine grid and solves the smooth remainder on coarser grids; O(n) elliptic solves at any resolution.
›
Radix sort
search-sort · low: Non-comparison sort that distributes keys by 8-bit digits; several times faster than comparison sorts on large arrays of integers, floats or fixed-size keys.
›
Parallel prefix sum
search-sort · low: Work-efficient scan (Blelloch, decoupled look-back) on CPU SIMD and GPUs; stream compaction
Finite differences
numerics · low: Replace derivatives with weighted differences of grid values; simple stencils plus a stability condition (CFL) turn PDEs like heat, advection and waves into array loops.
›
d-ary heap
data-structures · low: Array heap with d children per node (d = 4 typical): half the binary heap's depth, siblings in one cache line, faster priority queues.
›
BFS and DFS
graphs · low: The two basic graph traversals; BFS gives hop distances and levels, DFS gives discovery/finish order for cycles, components and topological order.
›
Runge-Kutta 4
numerics · low: The classic four-stage, fourth-order ODE step; error drops 16× when the step halves, with no derivatives or past steps needed.
›
Newton root finding
numerics · low: Linearize at the guess and jump to the tangent root; quadratic convergence near a simple root, made robust by brackets (1D) or line search.
›
GJK and EPA
physics · low: GJK decides whether (and how far apart) two convex shapes are from their support functions alone; EPA expands its simplex into penetration depth and normal.
›
Sweep and prune
physics · low: Sort box endpoints along an axis and sweep: only intervals that overlap on that axis are tested; near-linear per frame thanks to temporal coherence.
›
PRNGs (PCG, xoshiro)
numerics · low: Small, fast, statistically strong non-cryptographic generators: PCG32 and xoshiro256**, with seeding, parallel streams and unbiased ranges.
›
Spline interpolation
numerics · low: Linear, bilinear/trilinear and cubic spline interpolation on grids and tables
Verlet / leapfrog
numerics · low: Half-kick, drift, half-kick: a second-order, time-reversible, symplectic integrator with one force evaluation per step whose energy error stays bounded for millions of steps.
›
Neighbor lists
physics · low: Cell lists plus Verlet buffer lists for O(n) short-range pair interactions
LU and Cholesky factorization
numerics · low: Factor A = PLU (any square matrix, partial pivoting) or A = LLᵀ (SPD) once in O(n³), then solve each right-hand side in O(n²).
›
Sparse matrices (CSR)
numerics · low: Compressed sparse row stores only nonzeros as row pointers, column indices and values; SpMV streams them once, so it is memory-bandwidth bound.
›
Fast hash functions
data-structures · low: Non-cryptographic hashes built from 64×64→128-bit multiplies and xor-shifts; pick by key size, trust level and whether the hash is persisted.
›
Fixed timestep loop
graphics · low: Fixed simulation dt with accumulator, render interpolation, spiral-of-death guard
Explicit Euler
numerics · low: Step an ODE forward by its current slope, y += h·f(t, y); first-order, one evaluation per step, the baseline every other integrator is measured against.
›
Thomas tridiagonal solver
numerics · low: O(n) tridiagonal linear solve used in implicit finite-difference and spline schemes
Copy for AI
Similar systems
Share the most building blocks with this one.
sph-solver
18 %
physics-engine
17 %
topology-optimization
15 %