Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Publish-subscribe (pub-sub) systems present the state of the art in information dissemination to multiple users.Current XML-based pub-sub systems provide users with considerable flexibility allowing the formulation of complex queries on the content as ll as the structure of the streaming messages. Messages that contain one or more matches for a given user profile (query) are forwarded to the user. Recently various approaches focused on accelerating XML path query filtering using dedicated hardware architectures, like FPGAs. Despite their very high throughput, FPGAs require extensive update time while their physical resource availability is also limited.   exploit the parallelism found in XPath filtering systems using GPUs instead, which are favorable platforms due to the massive parallelism found in their hardware architecture, alongside the flexibility and programmability of software. By utilizing properties of the GPU memory hierarchy  can match thousands of user profiles at high throughput, requiring minimal update time. Ecient common prefix optimizations are also applied to the query set. An extensive experimental evaluation shows an average speedup of 10x (up to 2.5 orders of magnitude) versus the state of the art software approaches.
['Roger Moussalli', 'Robert J. Halstead', 'Mariam Salloum', 'Walid A. Najjar', 'Vassilis J. Tsotras']
I am writing a research paper on a idea Efficient XML Path Filtering Using GPUs
[{"from": "human", "value": "I am writing a research paper on a idea Efficient XML Path Filtering Using GPUs"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Publish-subscribe (pub-sub) systems present the state of the art in information dissemination to multiple users.Current XML-based pub-sub systems provide users with considerable flexibility allowing the formulation of complex queries on the content as ll as the structure of the streaming messages. Messages that contain one or more matches for a given user profile (query) are forwarded to the user. Recently various approaches focused on accelerating XML path query filtering using dedicated hardware architectures, like FPGAs. Despite their very high throughput, FPGAs require extensive update time while their physical resource availability is also limited.   exploit the parallelism found in XPath filtering systems using GPUs instead, which are favorable platforms due to the massive parallelism found in their hardware architecture, alongside the flexibility and programmability of software. By utilizing properties of the GPU memory hierarchy  can match thousands of user profiles at high throughput, requiring minimal update time. Ecient common prefix optimizations are also applied to the query set. An extensive experimental evaluation shows an average speedup of 10x (up to 2.5 orders of magnitude) versus the state of the art software approaches."}]