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Version: develop

Linear Solver

Solving linear equations is a common task in scientific computing. Taichi provides basic direct and iterative linear solvers for various simulation scenarios. Currently, there are two categories of linear solvers available:

  1. Solvers built for SparseMatrix
  2. Solvers built for ti.field

Sparse linear solver

You may want to solve some linear equations using sparse matrices. Then, the following steps could help:

  1. Create a solver using ti.linalg.SparseSolver(solver_type, ordering). Currently, the factorization types supported on CPU backends are LLT, LDLT, and LU, and supported orderings include AMD and COLAMD. The sparse solver on CUDA supports the LLT factorization type only.
  2. Analyze and factorize the sparse matrix you want to solve using solver.analyze_pattern(sparse_matrix) and solver.factorize(sparse_matrix)
  3. Call x = solver.solve(b), where x is the solution and b is the right-hand side of the linear system. On CPU backends, x and b can be NumPy arrays, Taichi Ndarrays, or Taichi fields. On the CUDA backend, x and b must be Taichi Ndarrays.
  4. Call solver.info() to check if the solving process succeeds.

Here's a full example.

import taichi as ti

arch = ti.cpu # or ti.cuda
ti.init(arch=arch)

n = 4

K = ti.linalg.SparseMatrixBuilder(n, n, max_num_triplets=100)
b = ti.ndarray(ti.f32, shape=n)

@ti.kernel
def fill(A: ti.types.sparse_matrix_builder(), b: ti.types.ndarray(), interval: ti.i32):
    for i in range(n):
        A[i, i] += 2.0

        if i % interval == 0:
            b[i] += 1.0

fill(K, b, 3)

A = K.build()
print(">>>> Matrix A:")
print(A)
print(">>>> Vector b:")
print(b)
# outputs:
# >>>> Matrix A:
# [2, 0, 0, 0]
# [0, 2, 0, 0]
# [0, 0, 2, 0]
# [0, 0, 0, 2]
# >>>> Vector b:
# [1. 0. 0. 1.]
solver = ti.linalg.SparseSolver(solver_type="LLT")
solver.analyze_pattern(A)
solver.factorize(A)
x = solver.solve(b)
success = solver.info()
print(">>>> Solve sparse linear systems Ax = b with the solution x:")
print(x)
print(f">>>> Computation succeed: {success}")
# outputs:
# >>>> Solve sparse linear systems Ax = b with the solution x:
# [0.5 0.  0.  0.5]
# >>>> Computation was successful?: True

Examples

Please have a look at our two demos for more information:

  • Stable fluid: A 2D fluid simulation using a sparse Laplacian matrix to solve Poisson's pressure equation.
  • Implicit mass spring: A 2D cloth simulation demo using sparse matrices to solve the linear systems.
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