Shrinking the Data to Iterate Through by Using Parallel Arrays
Learn to iterate through data using parallel arrays to optimize performance.
We'll cover the following
Iterating using parallel arrays
Next, we are going to try a more aggressive way of shrinking the amount of data we need to iterate through by using parallel arrays. First, a warning: this is an optimization that, in many cases, has too many drawbacks to be a viable alternative. Don't take this as a general technique and apply it without thinking twice. We will come back to the pros and cons of parallel arrays after looking at a few examples.
By using parallel arrays, we simply split the large structures into smaller types, similar to what we did with the authentication information for our User
class. But instead of using pointers to relate objects, we store the smaller structures in separate arrays of equal size. The smaller objects in the different arrays that share the same index form the complete original object.
An example will clarify this technique. The User
class we have worked with consists of 40 bytes. It now only contains a username string, a pointer to the authentication information, an integer for the current level, and the is_playing_
boolean. By making the user objects smaller, we saw that the performance improved when iterating over the objects. The memory layout of an array of user objects would look something like the one shown in the following figure:
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