Code Generation of Matrices and Arrays - MATLAB & Simulink (original) (raw)

MATLAB® stores matrix data and arrays (1–D, 2–D, ...) in column-major format as a vector. Simulink® and the code generator can store array data in column-major or row-major format. For an array stored in column-major layout, the elements of the columns are contiguous in memory. In row-major layout, the elements of the rows are contiguous. Array layout is also referred to as order, format, and representation. The order in which elements are stored can be important for integration, usability, and performance. Certain algorithms perform better on data stored in a particular order.

Programming languages and environments assume a single array layout for all data. MATLAB and Fortran use column-major layout by default, whereas C and C++ use row-major layout. With Simulink Coder™, you can generate C/C++ code that uses row-major layout or column-major layout.

Array Storage in Computer Memory

Computer memory stores data in terms of one-dimensional arrays. For example, when you declare a 3-by-3 matrix, the software stores this matrix as a one-dimensional array with nine elements. By default, MATLAB stores these elements with a column-major array layout. The elements of each column are contiguous in memory.

Consider the matrixA:

A translates to an array of length 9 in this order:

A(1) = A(1,1) = 1; A(2) = A(2,1) = 4; A(3) = A(3,1) = 7; A(4) = A(1,2) = 2; A(5) = A(2,2) = 5;

and so on.

In column-major format, the next element of an array in memory is accessed by incrementing the first index of the array. For example, these element pairs are stored sequentially in memory:

• A(i) and A(i+1)
• B(i,j) and B(i+1,j)
• C(i,j,k) and C(i+1,j,k)

The matrix A is represented in memory by default with this arrangement:

In row-major array layout, the programming language stores row elements contiguously in memory. In row-major layout, the elements of the array are stored as:

You can store the N-dimensional arrays in column-major or row-major layout. In column-major layout, the elements from the first (leftmost) dimension or index are contiguous in memory. In row-major layout, the elements from the last (rightmost) dimension or index are contiguous.

For more information on the internal representation of MATLAB data, see MATLAB Data.

Code generation software uses column-major format by default for several reasons:

• The world of signal and array processing is largely in column-major array layout: MATLAB, LAPack, Fortran90, and DSP libraries.
• A column is equivalent to a channel in frame-based processing. In this case, column-major storage is more efficient.
• A column-major array is self-consistent with its component submatrices:
  • A column-major 2-D array is a simple concatenation of 1-D arrays.
  • A column-major 3-D array is a simple concatenation of 2-D arrays.
  • The stride is the number of memory locations to index to the next element in the same dimension. The stride of the first dimension is one element. The stride of the nth dimension element is the product of the sizes of the lower dimensions.
  • Row-major n-D arrays have their stride of 1 for the highest dimension. Submatrix manipulations are typically accessing a scattered data set in memory, which does not allow for efficient indexing.

C uses row-major format. MATLAB and Simulink use column-major format by default. You can configure the code generation software to generate code with a row-major array layout. If you are integrating external C code with the generated code, see the considerations listed in this table.

Code Generator Matrix Parameters

The compiled model file, _`model`_.rtw, represents matrices as character vectors in MATLAB syntax, without an implied storage format. This format enables you to copy the character vector out of an .rtw file, paste it into a MATLAB file, and have MATLAB recognize it.

Column-Major Layout

For example, the 3-by-3 matrix in the Constant block

is stored in _`model`_.rtw as

Parameter { Identifier "Constant_Value" LogicalSrc P0 Protected no Value [1.0, 4.0, 7.0, 2.0, 5.0, 8.0, 3.0, 6.0, 9.0] CGTypeIdx 18 ContainerCGTypeIdx 19 ReferencedBy Matrix(1,4) [[0, -1, 0, 0];] GraphicalRef Matrix(1,2) [[0, 1];] BHMPrmIdx 0 GraphicalSource [0, 1] OwnerSysIdx [0, -1] VarGroupIdx [1, 0] WasAccessedAsVariable 1 }

The _`model`__data.c file declares the actual storage for the matrix parameter. You can see that the format is in column-major layout.

Parameters _model__P = { /* Expression: [ [1,2,3] ; [4,5,6] ;[7,8,9]]

• Referenced by: '/Constant ' */ { 1.0, 4.0, 7.0, 2.0, 5.0, 8.0, 3.0, 6.0, 9.0 } };

Row-Major Layout

For example, the 3-by-3 matrix in the Constant block

is stored in _`model`_.rtw as

Parameter { Identifier "Constant_Value" LogicalSrc P0 Protected no Value [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0] CGTypeIdx 18 ContainerCGTypeIdx 19 ReferencedBy Matrix(1,4) [[0, -1, 0, 0];] GraphicalRef Matrix(1,2) [[0, 1];] BHMPrmIdx 0 GraphicalSource [0, 1] OwnerSysIdx [0, -1] VarGroupIdx [1, 0] WasAccessedAsVariable 1 }

The _`model`__data.h file declares the actual storage for the matrix parameter. You can see that the format is in row-major layout.

Parameters _model__P = { /* Expression: [ [1,2,3] ; [4,5,6] ;[7,8,9]]

• Referenced by: '/Constant ' */ { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 } };

Internal Data Storage for Complex Number Arrays

Simulink and code generator internal data storage formatting differs from MATLAB internal data storage formatting only in the storage of complex number arrays. In MATLAB, the real and imaginary parts are stored in separate arrays. In Simulink and the code generator, the parts are stored in an interleaved format. The numbers in memory alternate real, imaginary, real, imaginary, and so forth. This convention allows efficient implementations of small signals on Simulink lines, for Mux blocks, and other virtual signal manipulation blocks. For example, the signals do not actively copy their inputs, just the references.

Unsupported Blocks for Row-Major Code Generation

The code generator does not support these blocks for code generation in row-major array layout.

Continuous

• Action Port
• Derivative
• Integrator
• Integrator Limited
• Integrator, Second-Order
• Integrator, Second-Order Limited
• PID Controller
• PID Controller (2DOF)
• State-Space
• Transfer Fcn
• Transport Delay
• Variable Time Delay
• Variable Transport Delay
• Zero-Pole

User-Defined Functions

• Level-2 MATLAB S-Function

Sources

• From Spreadsheet

Signal Attributes

• IC

Discrete

The code generator does not support these blocks for code generation in row-major array layout if the Input processing block parameter is set toElements as channels (sample based) and the block is connected to a State Reader or State Writer block.

• Discrete Transfer Function
• Discrete Filter
• Discrete FIR Filter

Additional Limitations for Row-Major Code Generation

• Variable-size signals are not supported for row-major code generation.
• The Stateflow® rising, falling, and crossing operators are not supported for row-major code generation.

Model Advisor Checks for Row-Major Code Generation

Array layout can be important for integration, usability, and performance. Programming languages and environments assume a single array layout for all data; you can generate C/C++ code that uses row-major layout. The code that you generate by using row-major algorithms performs with better speed and efficient memory usage when operating on data with row-major array layout.

To check that your model is configured for efficient row-major code generation and check the compatibility of existing elements with row-major code generation, use the Model Advisor checks in folder > . Checks include:

• Identify blocks generating inefficient algorithms
• Check for blocks not supported for row-major code generation
• Identify TLC S-Functions with unset array layout

See Also

• Code Generation of Matrices and Arrays
• Generate Row-Major Code for S-Functions
• Generate Row-Major Code for Model That Contains a MATLAB Function Block

Related Topics

• MATLAB Data
• Mapping MATLAB Types to Types in Generated Code
• Row-Major and Column-Major Array Layouts
• Dimension Preservation of Multidimensional Arrays
• Preserve Dimensions of Bus Elements in Generated Code
• Interface with Row-Major Data in MATLAB Function Blocks