Linear Algebra

Matrix and vector products

cupy.dot Returns a dot product of two arrays.
cupy.vdot Returns the dot product of two vectors.
cupy.inner Returns the inner product of two arrays.
cupy.outer Returns the outer product of two vectors.
cupy.matmul Returns the matrix product of two arrays and is the implementation of the @ operator introduced in Python 3.5 following PEP465.
cupy.tensordot Returns the tensor dot product of two arrays along specified axes.
cupy.einsum Evaluates the Einstein summation convention on the operands.
cupy.kron Returns the kronecker product of two arrays.

Decompositions

cupy.linalg.cholesky Cholesky decomposition.
cupy.linalg.qr QR decomposition.
cupy.linalg.svd Singular Value Decomposition.

Matrix eigenvalues

cupy.linalg.eigh Eigenvalues and eigenvectors of a symmetric matrix.
cupy.linalg.eigvalsh Calculates eigenvalues of a symmetric matrix.

Norms etc.

cupy.linalg.det Retruns the deteminant of an array.
cupy.linalg.norm Returns one of matrix norms specified by ord parameter.
cupy.linalg.matrix_rank Return matrix rank of array using SVD method
cupy.linalg.slogdet Returns sign and logarithm of the determinant of an array.
cupy.trace Returns the sum along the diagonals of an array.

Solving linear equations

cupy.linalg.solve Solves a linear matrix equation.
cupy.linalg.tensorsolve Solves tensor equations denoted by ax = b.
cupy.linalg.inv Computes the inverse of a matrix.
cupy.linalg.pinv Compute the Moore-Penrose pseudoinverse of a matrix.
cupy.linalg.tensorinv Computes the inverse of a tensor.
cupyx.scipy.linalg.solve_triangular Solve the equation a x = b for x, assuming a is a triangular matrix.