MATLAB Programming

Using Memory Efficiently
Numeric Arrays
MATLAB requires 1, 2, 4, or 8 bytes to store 8-bit, 16-bit, 32-bit, and 64-bit
signed and unsigned integers respectively. For floating-point numbers,
MATLAB uses 4 or 8 bytes for single and double types. To conserve
memory, The MathWorks recommends that you use the smallest integer or
floating-point type that will contain your data without overflowing. For more
information, see "Numeric Types" in the MATLAB Programming section on
Data Types.
Complex Arrays
MATLAB stores complex data as separate real and imaginary parts. If you
makeacopyofacomplexarrayvariable,andthenmodifyonlytherealor
imaginary part of the array, MATLAB creates a new array containing both
real and imaginary parts.
Sparse Matrices
It is best to store matrices with values that are mostly zero in sparse format.
Sparse matrices can use less memory and may also be faster to manipulate
than full matrices. You can convert a full matrix to sparse format using the
sparse function.
Compare two 1000-by-1000 matrices: X, a matrix of doubles with 2/3 of
itselementsequaltozero;andY, a sparse copy of X. Asshownbelow,
approximately half as much memory is required for the sparse matrix:
whos
Name Size Bytes Class
X 1000x1000 8000000 double array
Y 1000x1000 4004000 double array (sparse)
Memory Management Functions
The following functions can help you to manage memory use in MATLAB:
• whos shows how much memory has been allocated for variables in the
workspace.
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