flipud — Flip an array up-to-down along the first dimension.

flipud(A) mirrors A across its horizontal axis, reversing the order of rows (dimension 1). It works with scalars, vectors, matrices, N-D tensors, logical arrays, character arrays, string arrays, cell arrays, complex data, and gpuArray handles, matching MATLAB semantics.

Syntax

B = flipud(A)

• A is a scalar, vector, matrix, or N-D array. It may hold any MATLAB class: numeric, logical, complex, character, string, or cell. gpuArray inputs are supported and stay device-resident when the provider offers a flip hook.
• B is the same size and class as A with its first dimension reversed: B(i, :, ...) = A(end - i + 1, :, ...). All other dimensions are preserved. For arrays with more than two dimensions, higher pages are treated independently.
• flipud(A) is equivalent to flip(A, 1). Use fliplr(A) to reverse columns instead, or flip(A, dim) when you need a dimension other than 1 or 2.

How flipud works

• Always reverses dimension 1 (rows) and leaves all other dimensions untouched, even for rank > 2 data.
• Inputs with a single row (row vectors, scalars) are returned unchanged because the first dimension is singleton.
• Numeric, logical, complex, character, string, and cell arrays all retain their MATLAB types, layout, and metadata (including UTF-16 code units for char arrays).
• gpuArray inputs execute on the device via the generic flip provider hook (axis = 0); when that hook is unavailable, RunMat gathers once, mirrors the data on the host, and uploads the result so the returned value is still a gpuArray.
• Dimensions larger than ndims(A) are treated as singleton axes, so flipud never errors when A has rank < 1.
• Behaviour matches flip(A, 1) exactly; flipud is provided for readability and compatibility with existing MATLAB code.

How RunMat runs flipud on the GPU

RunMat first tries to execute flipud on the GPU by delegating to the provider’s generic flip implementation with axis 0 (zero-based). If the provider does not implement this hook, RunMat transparently gathers the tensor, performs the vertical flip on the host, and uploads the result back to the device so residency is preserved.

GPU memory and residency

You typically do not need to call gpuArray directly. RunMat’s auto-offload planner keeps tensors on the GPU when profitable and only gathers when a provider lacks the flip hook. Even in that fallback, flipud uploads the flipped result back to the device so subsequent operations remain gpu-resident.

Examples

Reverse Rows of a Matrix

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

Expected output:

B =
     7     8     9
     4     5     6
     1     2     3

Reverse a Column Vector

col = (1:4)';
rev = flipud(col)

Expected output:

rev =
     4
     3
     2
     1

Flip the First Dimension of a 3-D Tensor

T = reshape(1:24, [3 4 2]);
F = flipud(T)

Expected output:

F(:,:,1) =
     3     6     9    12
     2     5     8    11
     1     4     7    10

F(:,:,2) =
    15    18    21    24
    14    17    20    23
    13    16    19    22

Flip Characters in a Char Array Vertically

C = ['run'; 'mat'];
Cv = flipud(C)

Expected output:

Cv =
    'mat'
    'run'

Preserve Row Vector Orientation

row = 1:5;
same = flipud(row)

Expected output:

same = [1 2 3 4 5]

Keep gpuArray Results on the Device While Flipping Rows

G = gpuArray(rand(8, 8));
H = flipud(G);
isequal(gather(H), flipud(gather(G)))   % illustrative verification

FAQ

Related Array functions

Open-source implementation

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

• View flipud.rs on GitHub
• Learn how the runtime works
• Found a bug? Open an issue with a minimal reproduction.

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