Using GPUs for runtime monitoring and trace analysis

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Computer software is growing exponentially in size and thus complexity. Despite this growth in complexity, software still must be correct, which means that the software must comply with a given specification and is thus free of software defects. Runtime monitoring is a technique that checks the correctness of the software at run time on the deployed system. With the advent of general purpose computation on graphics processing units (GPUs), the question becomes how this new technology can be leveraged for runtime monitoring systems, especially in combination with trace analysis a combined approach. This project will investigate the use of GPU for runtime monitoring and accelerating algorithms for trace analysis, and develop novel recovery techniques using the independence of GPU systems from applications running on the main processor. These results will raise Canada's visibility in systems research and strength Canada's role in research. Besides the expected scientific publications, the industrial sponsor AMD agreed to help promote the developed library and tools if they meet AMD's requirements, that will further raise the impact of the project.