mod — Compute modulus values with MATLAB semantics in RunMat.
C = mod(A, B) computes remainders using the MATLAB definition A - B .* floor(A./B). Sign conventions, broadcasting, and complex-value behavior follow MATLAB semantics.
Syntax
R = mod(A, B)Inputs
| Name | Type | Required | Default | Description |
|---|---|---|---|---|
A | Any | Yes | — | Real dividend input (numeric/logical/char). |
B | Any | Yes | — | Real divisor input (numeric/logical/char). |
Returns
| Name | Type | Description |
|---|---|---|
R | NumericArray | Element-wise modulus result. |
Errors
| Identifier | When | Message |
|---|---|---|
RunMat:mod:InvalidInput | Inputs are complex or cannot be interpreted as real numeric, logical, or char operands. | mod: invalid input |
RunMat:mod:SizeMismatch | Operands are not broadcast-compatible. | mod: array sizes are not compatible for broadcasting |
RunMat:mod:Internal | Internal tensor conversion, allocation, or provider composition failed. | mod: internal error |
How mod works
- Works with MATLAB-style implicit expansion (broadcasting) between
AandB. - Returns
NaNfor elements whereBis zero or both arguments are non-finite in incompatible ways (Infmodulo finite,NaNinputs, etc.). - Logical and integer inputs are promoted to double precision; character arrays operate on their Unicode code points.
- Complex inputs use the MATLAB definition
mod(a, b) = a - b.*floor(a./b)with complex division and component-wisefloor. - Empty arrays propagate emptiness while retaining their shapes.
Does RunMat run mod on the GPU?
When both operands are GPU tensors with the same shape, RunMat composes mod from the provider hooks elem_div, unary_floor, elem_mul, and elem_sub. This keeps the computation on the device when those hooks are implemented (the shipped WGPU backend and in-process provider expose them). For mixed residency, shape-mismatched operands, or providers that lack any of these hooks, RunMat gathers to the host, applies the CPU implementation, and returns a host-resident result.
GPU memory and residency
Usually not. When the provider exposes the elementwise hooks noted above, mod executes entirely on the GPU. Otherwise RunMat gathers transparently, ensuring MATLAB-compatible behaviour without manual intervention. Explicit gpuArray / gather calls remain available for scripts that mirror MathWorks MATLAB workflows.
Examples
Computing the modulus of positive integers
r = mod(17, 5)Expected output:
r = 2Modulus with negative divisors keeps the divisor's sign
values = [-7 -3 4 9];
mods = mod(values, -4)Expected output:
mods = [-3 -3 0 -3]Broadcasting a scalar divisor across a matrix
A = [4.5 7.1; -2.3 0.4];
result = mod(A, 2)Expected output:
result =
[0.5 1.1;
1.7 0.4]Computing The Modulus Of Complex Numbers
z = [3 + 4i, -2 + 5i];
div = 2 + 1i;
res = mod(z, div)Expected output:
res =
[0.0 + 0.0i, 0.0 + 1.0i]Handling zeros in the divisor
warn = mod([2, 0, -2], [0, 0, 0])Expected output:
warn = [NaN NaN NaN]Using mod with character arrays
letters = mod('ABC', 5)Expected output:
letters = [0 1 2]Staying on the GPU when hooks are available
G = gpuArray(-5:5);
H = mod(G, 4);
cpuCopy = gather(H)Expected output:
cpuCopy = [3 0 1 2 3 0 1 2 3 0 1]Using mod with coding agents
Open a RunMat example with live inputs, then ask the agent to explain how mod changes the result.
Run a small mod example, explain the result, then change one input and compare the output.
FAQ
How is mod different from rem?⌄
mod uses floor and keeps the sign of the divisor. rem uses fix and keeps the sign of the dividend.
What happens when the divisor is zero?⌄
The result is NaN (or NaN + NaNi for complex inputs), matching MATLAB semantics.
Does mod support complex numbers?⌄
Yes. Both operands can be complex; the runtime applies MATLAB's definition with complex division and component-wise floor.
Do GPU sources need identical shapes?⌄
Yes. The device fast path currently requires both operands to share the same shape. Other cases fall back to the CPU implementation automatically.
Are empty arrays preserved?⌄
Yes. Empty inputs return empty outputs with the same shape.
Will mod ever change integer classes?⌄
Inputs promote to double precision internally; results are reported as double scalars or tensors, mirroring MATLAB's default numeric type.
Related Math functions
Elementwise
abs · angle · bsxfun · complex · conj · double · erf · erfcinv · exp · expm1 · factorial · flintmax · gamma · gammaln · heaviside · hypot · idivide · imag · intmax · intmin · ldivide · log · log10 · log1p · log2 · minus · nextpow2 · plus · pow2 · power · rdivide · real · realmax · realmin · realsqrt · rescale · sign · single · sqrt · swapbytes · times · typecast · uint16 · uint32 · uint8
Trigonometry
acos · acosh · asin · asinh · atan · atan2 · atanh · cos · cosd · cosh · cospi · deg2rad · pol2cart · rad2deg · sin · sind · sinh · sinpi · tan · tand · tanh
Reduction
all · any · bounds · cummax · cummin · cumprod · cumsum · cumtrapz · diff · gradient · max · maxk · mean · median · min · mink · movmax · movmean · movmedian · movmin · movprod · movstd · movsum · movvar · nnz · prod · rms · std · sum · trapz · var
Structure
bandwidth · isdiag · ishermitian · issymmetric · istril · istriu · symrcm
Signal
blackman · butter · buttord · cheb2ord · conv · conv2 · deconv · downsample · envelope · filter · filtfilt · fir1 · freqz · gauspuls · hamming · hann · hilbert · periodogram · pulstran · pwelch · rectpuls · resample · sawtooth · sinc · spectrogram · square · tripuls · unwrap · upsample · zplane
Optim
coneprog · fminbnd · fminunc · fsolve · fzero · integral · linprog · lsqcurvefit · lsqnonlin · optimoptions · optimset · quad · secondordercone
Ops
cross · ctranspose · dot · mldivide · mpower · mrdivide · mtimes · pagemtimes · pagetranspose · trace · transpose
Open-source implementation
Unlike proprietary runtimes, every RunMat function is open-source. Read exactly how mod is executed, line by line, in Rust.
- View the source for mod 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.