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:content {:text "AI-SPRINT will provide tools for developing learning as a service solution, that, starting from a training set with labelled training examples (images or temporal data series which are of interest for use cases) will automatically identify the most accurate deep neural network which provides execution time guarantees."},
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:content {:text "AI-SPRINT will explore solutions where the edge servers or the AI-enabled sensors run the initial layers of the neural network, and then send the output to the cloud to feed the remaining layers and produce the final result."},
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:content {:text "AI-SPRINT runtime environment will include tools to: i) support the continuous deployment of AI applications; "},
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:content {:text "i) support application components concurrent execution reacting to node failures and identifying their optimal placement and resource capacity"},
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:content {:text " iii) trigger automated model retraining, leveraging on solutions for training and retraining at the edge;"},
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:content {:text "v) optimize the scheduling and assignment of accelerator devices among competing training jobs."},
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:content {:text "Continuous deployment is the process where development, testing, delivery and progressive deployment of an application is considered as a whole, reducing operation and development costs"},
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:content {:text "This is especially important in a scenario where data is continuously retrieved, and AI models are retrained."},
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:content {:text "heterogeneity of the edge laye"},
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:content {:text "streamlined mechanisms to guide the process of configuring computing resources across the computing continuum"},
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:content {:text "https://www.egi.eu/services/cloud-compute"},
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:content {:text "ocker containers to automate deployment and provide the level of isolation needed to enforce performance constraints with minimal overhead."},
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:content {:text "OASIS TOSCA templates"},
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:content {:text "AI model architecture search"},
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:content {:text "AI cloud-edge application design"},
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:content {:text " CNNs for image recognition"},
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:content {:text "multi-objective perspective trading-off accuracy with energy consumption"},
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:content {:text "for edge device"},
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:content {:text " federated setting"},
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:content {:text "cloud orchestration runtime that deploys complex and customized virtual infrastructures on multiple back-ends"},
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:content {:text " edge limited capacity "},
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:content {:text "several approaches have been proposed to tackle this issue"},
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:content {:text "AI-SPRINT Objectives"},
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:extra {:page 7}}
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