Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Many large-scale applications simultaneously rely on multiple resources for efficient execution. For example, such applications may require both large compute and storage resources; hover, very few supercomputing centers can provide large quantities of both. Thus, data generated at the compute site oftentimes has to be moved to a remote storage site for either storage or visualization and analysis. Clearly, this is not an efficient model, especially when the two sites are distributed over a wide-area network.   Thus,  present a framework called "ParaMEDIC: Parallel Metadata Environment for Distributed I/O and Computing" which uses application-specific semantic information to convert the generated data to orders-of-magnitude smaller metadata at the compute site, transfer the metadata to the storage site, and re-process the metadata at the storage site to regenerate the output. Specifically, ParaMEDIC trades a small amount of additional computation (in the form of data post-processing) for a potentially significant reduction in data that needs to be transferred in distributed environments.
['Pavan Balaji', 'Wu-chun Feng', 'Heshan Lin']
I am writing a research paper on a idea Semantic-based distributed i/o with the paramedic framework
[{"from": "human", "value": "I am writing a research paper on a idea Semantic-based distributed i/o with the paramedic framework"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Many large-scale applications simultaneously rely on multiple resources for efficient execution. For example, such applications may require both large compute and storage resources; hover, very few supercomputing centers can provide large quantities of both. Thus, data generated at the compute site oftentimes has to be moved to a remote storage site for either storage or visualization and analysis. Clearly, this is not an efficient model, especially when the two sites are distributed over a wide-area network.   Thus,  present a framework called \"ParaMEDIC: Parallel Metadata Environment for Distributed I/O and Computing\" which uses application-specific semantic information to convert the generated data to orders-of-magnitude smaller metadata at the compute site, transfer the metadata to the storage site, and re-process the metadata at the storage site to regenerate the output. Specifically, ParaMEDIC trades a small amount of additional computation (in the form of data post-processing) for a potentially significant reduction in data that needs to be transferred in distributed environments."}]