RunMat
GitHub

View all functions

CategoryMath: Trigonometry
GPUYes

What does the sin function do in MATLAB / RunMat?

y = sin(x) evaluates the sine of each element in x, using radians and preserving MATLAB’s column-major layout and broadcasting rules.

How does the sin function behave in MATLAB / RunMat?

  • Operates on scalars, vectors, matrices, and N-D tensors with MATLAB-compatible implicit expansion.
  • Logical and integer inputs are promoted to double precision before evaluation so that downstream arithmetic matches MATLAB’s numeric tower.
  • Complex values use the analytic extension sin(a + bi) = sin(a)cosh(b) + i·cos(a)sinh(b) while propagating NaN/Inf components independently.
  • Character arrays are interpreted through their Unicode code points and return dense double arrays that mirror MATLAB’s behaviour.
  • Appending 'like', prototype mirrors the prototype’s class and residency (host or GPU), re-uploading the result when a device prototype is supplied.
  • Empty inputs and singleton dimensions are preserved without introducing extraneous allocations.

sin Function GPU Execution Behaviour

  • With RunMat Accelerate active, tensors remain on the device and execute through the provider’s unary_sin hook (or fused elementwise kernels) without leaving GPU memory.
  • If the provider declines the operation—for example, when only CPU precision is available or the operand type is unsupported—RunMat transparently gathers to the host, computes the result, and reapplies the requested residency rules (including 'like' prototypes).
  • Fusion planning keeps neighbouring elementwise operators grouped, reducing host↔device transfers even when an intermediate fallback occurs.

Examples of using the sin function in MATLAB / RunMat

Computing the sine of a scalar

y = sin(pi/2);

Expected output:

y = 1

Computing the sine of a vector

angles = [0 pi/6 pi/4 pi/3];
values = sin(angles);

Expected output:

values = [0 0.5 0.7071 0.8660]

Computing the sine of a complex number

z = sin(1 + 2i);

Expected output:

z = 3.1658 + 1.9596i

Computing the sine of a matrix on a GPU

A = reshape(0:5, [3 2]);
G = gpuArray(A);
R = sin(G);
result = gather(R);

Expected output:

result =
         0    0.1411
    0.8415   -0.7568
    0.9093   -0.9589

Keeping results on the GPU with a 'like' prototype

proto = gpuArray.zeros(1, 1, 'single');
angles = [0 pi/2];
deviceResult = sin(angles, 'like', proto);
gathered = gather(deviceResult);

Expected output:

gathered =
  1x2 single
     0     1

GPU residency in RunMat (Do I need gpuArray?)

You usually do not need to call gpuArray explicitly. The fusion planner keeps tensors on the GPU whenever the active provider exposes the necessary kernels (such as unary_sin). Manual gpuArray / gather calls remain supported for MATLAB compatibility or when you need to pin residency before interacting with external code.

FAQ

When should I use the sin function?

Whenever you need the elementwise sine for signals, control systems, geometry, or any workflow that depends on periodic functions across scalars, vectors, or higher-dimensional tensors.

Does sin expect radians or degrees?

Radians are required, just like in MATLAB. Use sin(deg2rad(theta)) or the sind builtin if you want to work in degrees.

How are logical, integer, or character inputs handled?

Logical and integer inputs are promoted to double precision before evaluation, and character arrays are converted to their Unicode code points. The result is always floating-point, matching MATLAB’s behaviour.

Can the result stay on the GPU automatically?

Yes. If your inputs are already on the GPU—or you pass 'like', gpuArray(…)—RunMat keeps the output on the device. When a fallback is required, the runtime re-uploads the result so downstream consumers still see a GPU tensor.

What happens if the provider does not implement unary_sin?

RunMat gathers the tensor to the host, computes sin with the reference implementation, and applies the requested residency rules (including 'like' re-uploads) before returning.

Does sin support complex numbers?

Absolutely. Real and imaginary parts are handled according to the analytic extension, and NaNs/Infs propagate component-wise exactly as in MATLAB.

Can I use complex prototypes with 'like'?

Not yet. Provide real-valued prototypes (host or GPU) when using 'like'; complex prototypes raise a descriptive error so you can fall back to the default output rules.

See Also

cos, tan, gpuArray, gather

Source & Feedback