Optimizing script language performance with custom memory allocators

The last weekend I did some exploration on the script language execution performance. Specifically on the memory allocation side of things, and I would like to share my findings.

Script languages and memory usage

As you probably know script languages (most of them at least, like Python, Lua, etc) have the tendency to make a huge amount of small allocations on the heap. Almost everything is stored on the heap, and if you care for performance, you start to feel homesick about your beloved C stack! Anyway, nothing comes for free, and scripting languages have to take something from you in exchange for all the goods it gives you back. So the best you can do is make sure that you have the best memory allocator for the job.

Doing too many small allocations and releases on the heap can create memory fragmentation, along with all the evil that comes with this. The common approach is to create a specialized memory allocator that serves small and constant in size blocks of memory to the scripting language, taken from a bigger chunk of memory reserved from the system. This is a common in all “realtime” and intencive applications like games, and something I did many times to gain performance.

Can’t beat the standard malloc

What I discovered with my latest attempt was that it has gotten quite hard to beat the GNU implementation of malloc(). Something that used to be easy in the past when you focused on a specialized case (e.g. small blocks of memory). Not that you can’t do better if you try hard, but at this point the malloc() implementation is already super-fast for 99.9% of applications on the desktop. Rest asured that you will not be able to do much better. However that is not the case for embedded devices that don’t share the same virtual memory benefits as the desktop computers.

My hand tuned specialized memory allocator for small blocks of memory ( <= 256bytes ) was not able to be more that 1% faster that the native malloc() on the OS X 10.6. However on the iPhone the same allocator was twice as fast as the native malloc() ! Since the target was from the begining the iPhone that seemed like big win! However when I set up a small benchmark in the scripting environment that did some allocations of game engine objects and released then again in various patterns, the results were disappointing. The gain from using my specialized (and twice as fast) allocator resulted in improvement of about 5% in execution speed in a memory intensive benchmark. And at some tests even slower! That was odd and most of all not good!

Why I was failing

After some inspections and tests that made the case of me doing something really stupid less probable, I narrowed down the cause.

In most cases of using a scripting language you have some classes defined in C++ that you instatiate in the scripting language. Take for example a 3D vector class “CVector3” defined in C++. When you instatiate this in the script language you get two allocations. One in the scripting language that allocates the “proxy” object and one in the C++ environment. When giving a new allocator to the scripting language to do its allocations you only “optimize” the first allocation. The one in C++ still goes through the system default allocator.

And since you optimize half of the allocations you expect to have half the performance boost… well… wrong. It turns out that you can even be slower this way. The secret here is the CPU cache. By doing the above, you have two memory blocks that are usually accessed together, but are far apart in memory. This can really hurt performance badly on a device with slow memory like the iPhone.

The solution

The solution was of course to use the same allocator on the C++ side by overriding the “new” operator of the class. This made the blocks of memory allocated on the script side to be close to the block allocated on the C++ side. This way access to the object only involves accessing one part of the memory and giving nice cache hits. Performance up by 30%, which was nice and expected.

One other interesting thing that I found from this is that, on the iPhone, if I just override the “new” operator of a class and make it allocate the memory with plain malloc() and don’t use my allocator at all, the system is again faster!

This is probably from the fact that “new” does not go through plain malloc() (didn’t bother to check) as the scripting language environment does. So the allocated blocks end up in differect arenas at different parts of the memory, with the result of losing performance for the same reason as above!

So, keep your related allocations close together when crossing the language barrier!

My First Contribution to Django


about 2 weeks ago I created a multilingual version slugify for django! You can find the code here.

What is slugify? It the function that gets us from “This is my post” to “this-is-my-post” and its used widely on the web to make human friendly URLs, where the data are not accessed by their numerical ID but by the human readable “slug”.

Django provides a function to automatically create the slug from a phrase. However that only worked for English characters. Any extended character in unicode was ignored, which resulted in empty slugs if the language was other than English.

The “downcode” function I provided maps characters in other languages to English ones. Which allows to use the slygify function that comes with Django!

Multithreaded Game Scripting with Stackless Python

The very basic problem that a creator of a game engine faces when it comes to scripting the game engine is: what will be the language that will be used. Of cource there is the option of creating a custom language for the purpose, but today with the plethora of scripting languages available it doesn’t really make sense to go through all the development process of a custom scripting language. No matter how big the development team will be, it will never be possible to match the man-months that have gone into an existing scripting language.

I will try to introduce the scripting language Python and more specifically a special version of it, the Stackless Python, as I used it in the implementation of the Sylphis3D Game Engine. For a basic introduction to game programming with python I suggest you try this book : Game Programming with Python. Continue reading