minus — Compute element-wise subtraction in MATLAB and RunMat.

minus(A, B) (or A - B) subtracts corresponding elements of B from A. Implicit expansion and complex handling follow MATLAB semantics.

Syntax

C = minus(A, B)
C = minus(A, B, "like", prototype)

Inputs

Returns

Errors

How minus works

• Supports real, complex, logical, and character inputs; logical and character data are promoted to double precision before subtraction.
• Implicit expansion works across any dimension, provided the non-singleton extents match. Size mismatches raise the standard MATLAB-compatible error message.
• Complex operands follow MATLAB's analytic rule (a + ib) - (c + id) = (a - c) + i(b - d).
• Empty dimensions propagate naturally—if either operand has a zero-sized dimension after broadcasting, the result is empty with the broadcasted shape.
• Integer inputs promote to double precision before subtraction, mirroring MATLAB behaviour and keeping numeric tower rules consistent with other RunMat arithmetic builtins.
• The optional 'like' prototype makes the output adopt the residency (host or GPU) and complexity characteristics of the prototype, which is particularly useful for keeping implicit-expansion expressions on the device.

Does RunMat run minus on the GPU?

When a gpuArray provider is active:

1. If both operands are gpuArrays with identical shapes, RunMat dispatches to the provider's elem_sub hook, including for complex-interleaved resident handles. 2. If the left operand is a gpuArray and the right operand is a real scalar, RunMat calls scalar_sub to keep the computation on the device. 3. If the right operand is a gpuArray and the left operand is a real scalar, RunMat calls scalar_rsub so the scalar subtraction also remains on the device. 4. For shape-compatible implicit expansion, RunMat first expands gpuArray operands on device with repmat and then dispatches elem_sub. 5. Unsupported shapes or operand kinds gather transparently to host memory, compute the result with full MATLAB semantics, and return a host tensor unless a 'like' GPU prototype is supplied—in which case the runtime re-uploads the output to honour the residency request.

GPU memory and residency

RunMat's auto-offload planner keeps tensors on the GPU whenever fused expressions benefit from device execution. Explicit gpuArray / gather calls remain supported for MATLAB code that manages residency manually. When the active provider lacks the kernels needed for a particular call (for example, implicit expansion between gpuArrays of different shapes), RunMat gathers back to the host, computes the MATLAB-accurate result, and resumes execution seamlessly.

Examples

Subtracting two matrices element-wise

A = [7 8 9; 4 5 6];
B = [1 2 3; 1 2 3];
D = minus(A, B)

Expected output:

D =
     6     6     6
     3     3     3

Subtracting a scalar from every matrix element

A = magic(3);
shifted = minus(A, 0.5)

Expected output:

shifted =
    7.5    0.5    5.5
    2.5    4.5    6.5
    3.5    8.5    1.5

Broadcasting a column minus a row vector

col = (1:3)';
row = [10 20 30];
M = minus(col, row)

Expected output:

M =
    -9   -19   -29
    -8   -18   -28
    -7   -17   -27

Subtracting complex numbers element-wise

z1 = [1+2i, 3-4i];
z2 = [2-1i, -1+1i];
diffz = minus(z1, z2)

Expected output:

diffz =
    -1 + 3i     4 - 5i

Subtracting from character codes

letters = 'DEF';
codes = minus(letters, 1)

Expected output:

codes = [67 68 69]

Keeping element-wise differences on the GPU with 'like'

proto = gpuArray.zeros(1, 1);
G1 = gpuArray([10 20 30]);
G2 = gpuArray([1 2 3]);
deviceDiff = minus(G1, G2, 'like', proto);
result = gather(deviceDiff)

Expected output:

deviceDiff =
  1x3 gpuArray
     9    18    27
result =
     9    18    27

Using minus with coding agents

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

FAQ

Related Math functions

Open-source implementation

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

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

About RunMat

RunMat is an open-source runtime that executes MATLAB-syntax code blazing on any GPU. It is licensed under the Apache 2.0 license.

• RunMat automatically optimizes your math for GPU execution on Apple, Nvidia, and AMD hardware. No code changes needed. Simulations that took hours now take minutes.
• Start running code in seconds. RunMat runs in the browser, on the desktop, or from the CLI. No license server, no IT ticket.

Getting started · Benchmarks · Pricing