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FedScale

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About

FedScale is a scalable and extensible federated learning (FL) engine that provides high-level APIs for implementing FL algorithms and deploying them across various hardware and software backends. It includes a comprehensive range of datasets for evaluating FL tasks from image classification to language modeling. FedScale offers extensive benchmarking capabilities with realistic datasets that simulate real-world scenarios where FL solutions are applied. The platform supports multiple backends, including mobile devices, local laptops, and clusters on GPUs/CPUs, facilitating efficient FL benchmarking. Its extensible design allows for easy implementation of new FL algorithms and systems techniques, enabling fair comparisons against state-of-the-art solutions across numerous datasets.

Platform
Web
Keywords
machine learningscalabledatasetsfederated learningbenchmark
Task
federated learning
Features

• high-level apis for fl algorithms

• support for diverse hardware backends

• comprehensive datasets for evaluation

• benchmarking capabilities

• extensible design for new algorithms

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