MATLAB Programming Fundamentals - MathWorks

Strategies for Efficient Use of Memory

In this section...

“Ways to Reduce the Amount of Memory Required” on page 29-2

“Using Appropriate Data Storage” on page 29-4

“How to Avoid Fragmenting Memory” on page 29-7

“Reclaiming Used Memory” on page 29-8

Ways to Reduce the Amount of Memory Required

The source of many "out of memory" problems often involves analyzing or processing an

existing large set of data such as in a file or a database. This requires bringing all or part

of the data set into the MATLAB software process. The following techniques deal with

minimizing the required memory during this stage.

Load Only as Much Data as You Need

Only import into MATLAB as much of a large data set as you need for the problem you are

trying to solve. This is not usually a problem when importing from sources such as a

database, where you can explicitly search for elements matching a query. But this is a

common problem with loading large flat text or binary files. Rather than loading the

entire file, use the appropriate MATLAB function to load parts of files.

File Type Partial Loading

MAT-file Load part of a variable by indexing into an

object that you create with the matfile

function.

Text Use the textscan function to access parts

of a large text file by reading only the

selected columns and rows. If you specify

the number of rows or a repeat format

number with textscan, MATLAB

calculates the exact amount of memory

required beforehand.

29 Memory Usage