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TF2AIF: Facilitating development and deployment of accelerated AI models on the cloud-edge continuum
April 23, 2024, 4:42 a.m. | Aimilios Leftheriotis, Achilleas Tzenetopoulos, George Lentaris, Dimitrios Soudris, Georgios Theodoridis
cs.LG updates on arXiv.org arxiv.org
Abstract: The B5G/6G evolution relies on connect-compute technologies and highly heterogeneous clusters with HW accelerators, which require specialized coding to be efficiently utilized. The current paper proposes a custom tool for generating multiple SW versions of a certain AI function input in high-level language, e.g., Python TensorFlow, while targeting multiple diverse HW+SW platforms. TF2AIF builds upon disparate tool-flows to create a plethora of relative containers and enable the system orchestrator to deploy the requested function on …
abstract accelerators ai models arxiv cloud coding compute cs.lg current deployment development edge evolution function multiple paper technologies tool type versions
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