A new physics engine with automatic process distribution between CPU-GPU
Sandbox '08 Proceedings of the 2008 ACM SIGGRAPH symposium on Video games
An adaptative game loop architecture with automatic distribution of tasks between CPU and GPU
Computers in Entertainment (CIE) - SPECIAL ISSUE: Games
Processing data streams with hard real-time constraints on heterogeneous systems
Proceedings of the international conference on Supercomputing
Scheduling processing of real-time data streams on heterogeneous multi-GPU systems
Proceedings of the 5th Annual International Systems and Storage Conference
Arbiter work stealing for parallelizing games on heterogeneous computing environments
Proceedings of the High Performance Computing Symposium
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The increase of computational power of programmable GPU (Graphics Processing Unit) brings new concepts for using these devices for generic processing. Hence, with the use of the CPU and the GPU for data processing come new ideas that deals with distribution of tasks among CPU and GPU, such as automatic distribution. The importance of the automatic distribution of tasks between CPU and GPU lies in three facts. First, automatic task distribution enables the applications to use the best of both processors. Second, the developer does not have to decide which processor will do the work, allowing the automatic task distribution system to choose the best option for the moment. And third, sometimes, the application can be slowed down by other processes if the CPU or GPU is already overloaded. Based on these facts, this paper presents new schemes for efficient automatic task distribution between CPU and GPU. This paper also includes tests and results of implementing those schemes with a test case and with a real-time system.