Designing the Framework of a Parallel Game Engine 1.4
1. Introduction
With the advent of multiple cores within a processor the need to create a parallel game engine has become more and more important. It is still possible to focus primarily on just the GPU and have a single threaded game engine, but the advantage of utilizing all the processors on a system, whether CPU or GPU, can give a much greater experience for the user. For example, by 
utilizing more CPU cores a game could increase the number of rigid body physics object for greater effects on screen, or developing smarter AI that gives it a more human like behavior.
1.1. Overview
The “Parallel Game Engine Framework” or engine is a multi-threaded game engine that is designed to scale to as many processors as are available within a platform. It does this by executing different functional blocks in parallel so that it can utilize all available processors. This is easier said than done as there are many pieces to a game engine that often interact with one another and can cause many threading errors because of that. The engine takes these scenarios into account and has mechanisms for getting proper synchronization of data without having to be bound by synchronization locks. The engine also has a method for executing data synchronization in parallel in order to keep serial execution time at a minimum.
1.2. Assumptions
This paper assumes a good working knowledge of modern computer game development as well as some experience with game engine threading or threading for performance in general.
2. Parallel Execution State
The concept of a parallel execution state in an engine is crucial to an efficient multi-threaded runtime. In order for a game engine to truly run parallel, with as little synchronization overhead as possible, it will need to have each system operate within its own 
execution state with as little interaction as possible to anything else that is going on in the engine. Data still needs to be shared however, but now instead of each system accessing a common data location to say, get position or orientation data, each system has its own copy. This removes the data dependency that exists between different parts of the engine. Notices of any changes made by a system to shared data are sent to a state manager which then queues up all the changes, called messaging. Once the different systems are done executing, they are notified of the state changes and update their internal data structures, which is also part of messaging. Using this mechanism greatly reduces synchronization overhead, allowing systems to act more independently.
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Source: Intel® Software Network
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