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The current projects reflect the current research interests of the group lead and form the core research directions of NSG. The previous projects reflect earlier research experiences that helped shape the research philosophy of NSG, but they are not among the group's current focus areas. |
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In-network machine learning (ML) refers to mapping trained machine learning inference models to programmable devices. This project aims to make in-network ML a practical service. The project covers various aspects of in-network ML, including efficient algorithm mapping, rapid model deployment, hybrid deployment, use cases, and others. |
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In-network computing offloads server-based applications to programmable devices. However, network devices are very resource-constrained compared to servers. This project aims to scale in-network computing algorithms further via distributed deployment. This project can also be used as an extension of the in-network ML project. |