kron — Compute Kronecker products in MATLAB and RunMat.

kron(A, B) forms the Kronecker (tensor) product of A and B. Output sizing and column-major block ordering follow MATLAB semantics.

Syntax

C = kron(A, B)

Inputs

Returns

Errors

How kron works

• Works with scalars, vectors, and matrices. Higher-rank tensor inputs are a RunMat extension and are rejected while strict compatibility mode disables extensions.
• If either input is complex, the output is complex and uses MATLAB's complex arithmetic rules.
• Logical and char inputs are promoted to double precision before multiplication.
• All eight integer classes are supported. Integer operands must have the same class, or the other operand must be a scalar double; multiplication preserves the integer class and saturates on overflow. Complex integer arithmetic is rejected.
• Scalar arguments act as uniform scalars (kron(a, B) behaves like a * B).
• Empty dimensions propagate; if any replicated dimension is zero, the result is empty along that axis.
• Invalid inputs (non-numeric/non-logical, or values that would overflow the maximum size) raise descriptive MATLAB-style errors.

Does RunMat run kron on the GPU?

For real floating-point operands, RunMat uses the exact owning provider's kron hook when the operands share a compatible device and precision; mixed host/resident floating inputs may upload the host operand temporarily and use the same path. Provider outputs are validated for shape, ownership, device, storage, precision, and non-aliasing. Typed-integer and otherwise unsupported cases gather automatically, compute with class-preserving host semantics, and restore the result to the source provider when possible. An explicit gpuArray source must remain resident or the call errors, while automatically resident values may return to host only when their class cannot be represented safely.

GPU memory and residency

You usually do not need to call gpuArray explicitly. RunMat's planner keeps values resident on the GPU whenever it is profitable. Explicit gpuArray calls remain supported for MATLAB compatibility and for users who want direct control over residency.

Examples

Computing the Kronecker product of two matrices

A = [1 2; 3 4];
B = [0 5; 6 7];
C = kron(A, B)

Expected output:

C =
     0     5     0    10
     6     7    12    14
     0    15     0    20
    18    21    24    28

Kronecker product with row and column vectors

row = [1 2 3];
col = (1:3)';
K = kron(row, col);
size(K)

Expected output:

ans =
     3     9

Scaling a matrix with a scalar using kron

A = [1 2; 3 4];
S = kron(2, A)

Expected output:

S =
     2     4
     6     8

Building block-diagonal systems with kron

I = eye(3);
M = [1 0; 0 -1];
blockDiag = kron(I, M)

Kronecker product of complex matrices

A = [1+2i 0; 0 3-1i];
B = [0 1; 2 3i];
C = kron(A, B)

Using kron with logical masks

mask = logical([1 0; 0 1]);
tile = kron(mask, ones(2))

Running kron on GPU-resident tensors

G = gpuArray(rand(2));
H = gpuArray([1 -1; -1 1]);
K = kron(G, H);
isgpuarray(K)

Expected output:

ans = logical 1

Using kron with coding agents

Open a RunMat example with live inputs, then ask the agent to explain how kron changes the result.

FAQ

Related Array functions

Open-source implementation

Unlike proprietary runtimes, every RunMat function is open-source. Read exactly how kron is executed, line by line, in Rust.

• View the source for kron in Rust on GitHub
• Learn how the RunMat runtime works
• Found a bug? Open an issue with a minimal reproduction.

About RunMat

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