Category: GBC Object Pool

The latest update to GBC Object Pool now supports the passing of parameters to your create and return functions! By passing in a table of key/value pairs, you can reduce the amount of create and return functions needed when creating object pools.

Previously, you had to code a separate create function for every pool you created. Seems like a lot of code for creating similar objects.

Check out this example below:

Old Way

New Way

In the example above, using the old method, you had to code a new create function for every pool you wanted to use.  This was a lot of code, especially for pooled objects that had very similar, but different, settings. Notice that friction and bounce settings are slightly different.  Same with your return to pool function. It gets worse as you add more pools.

Using the new method, we use a single create function to create multiple image pools, and pass in parameters that are used to modify physics properties for the pool. We also add an id field to each image to show that you can create your own fields to store data in each object.

Another example demonstrates passing in the name of the actual image into the create function:

In the example above, we use a common create function to create an image with physics properties. Passing in the parameters for the actual image to use allows us to have a single, generic create function instead of creating multiple functions to create your pool.

Examples Available

Check out the GBC Object Pool Git for source code and compiled examples.  If you have any questions, I am available in the Corona Forums.

GBC Object Pool is a CoronaSDK plugin that simplifies the management of Object Pooling. In this article, I describe the method to pool complex physics objects.

A complex physics object consists of several display objects connected together by a physics joint. I recently added another example to the GBC Object Pool sample app that demonstrates how to pool complex physics objects. This article will go through some of the code in that example.

Using the traditional way of object creation, you would need to create multiple objects and joints in order to display a complex physics object. Depending on the complexity of this object, there may be visible performance issues (screen stutter or delay) when creating these types of objects. Utilizing object pooling will reduce or eliminate this delay.

The general solution is to create as many pools that are needed in order to create the object, and then join them via joints after you extract them from the pool. For example, connecting similar items may only require one pool. In the example, though, we connect three circles to a square, so I created two pools… every time we wish to display this type of complex object (when we tap on the screen), we grab one square from the square pool and three circles from the circle pool, and join them together.

We need a way to track all the objects used, so we can return them to the pool later. Notice above, we save a reference to the joints and circles in the square object itself. Since the square object will contain a listener that will start removing everything when tapped, it’s a great place to store it.

The code below is the listener that is called when you tap the square. This function will dismantle the complex object and return the parts to their appropriate pool.

That’s really all there is to it. In summary, just remember:

• When creating a complex object
  • Grab the objects from the pools
  • Create your physics joints
  • Store a reference to all the objects and joints used
• To remove a complex object
  • Remove the joints using display:remove(joint) or joint:removeSelf()
  • Return all items to the appropriate pools

The sample app included in my GBC Object Pool plugin has a performance scene that compares object pooling to traditional object creation. I took that scene, and modified it to execute 100 times automatically. After each run, it dumped the amount of time it took to execute.

Here are the results I experienced using the following settings in the app:

• Display 100 images, 200 times
• Use colors, physics, and scaling
• Display the images using traditional methods, then pooling. Record both times
• Repeat 100 times

Note that while the app is running, I did not attempt to access the devices, and no other apps were running in the background. Basically, I ran the app, clicked Start, and walked away.

Windows Desktop Performance

For this test, I used my development machine… a 2 year old Dell XPS 8700 with 16GB RAM.

Notice the tightness of the pooling times? GBC Object Pool (and object pooling in general) is pretty consistent, operating on average around 6700 milliseconds to perform the task.

The blue dots represents the traditional method of creating 200 images via display.newImageRect() 100 times, and then removing them. Notice the sporadic times and wide distribution. The dotted line represents a linear average where 50% percent of the dots are above the line and 50% are below the line. Notice that all of the object pooling tests are mapped below this line.

Android Performance

Moving on to smart devices, I used my Android phone… a 2+ year old mid-range Samsung.

Again, notice how pooling provides a more consistent result and maps faster than traditional average times?

What is interesting is the first few items between run 1 and run 10 (and again between run 61 and 75). Check out the data listed here:

Something definitely was happening on the phone (memory allocation? background OS task?), but you will notice that it wasn’t a noticeable factor when using pooling. Since it is not possible to know when or if a background task will start executing while a user is playing your game, I would expect the game to stutter if you were creating a lot of objects during this time via the traditional method.