Collaborative Research: CNS Core: Medium: A Stateful Switch Architecture for In-Network Compute
- Institution
- Regents of the University of Michigan - Ann Arbor, MI
- Principal investigator
- Muhammad Shahbaz
- Funding
- $240K
- Duration
- 2025–2026
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Abstract
Today's cloud data centers struggle to keep up with the computing demands of big-data applications (e.g., social media, video streaming, and artificial intelligence) that form the backbone of our modern technological society. The current status-quo of executing compute at the end-host servers while using networks for routing packets only, restricts these data centers from scaling to ever-growing distributed and high-performance computing (HPC) applications. In-network computing scales and accelerate modern applications by performing parts of the high-level computation directly inside the network switches. However, today’s switches implement simple, stateless packet protocols (e.g., routing and forwarding) and cannot perform complicated stateful operations needed to run distributed applications. To address this challenge, the proposal seeks to develop (1) a stateful switch architecture for flexible management, computation, and sharing of applications' state in the network, beyond just traditional packet processing; (2) a network-wide abstraction and runtime to program and operate the proposed stateful switches collectively within a data center; and, lastly, (3) a suite of representative applications and test cases to guide the design and implementation of these stateful switches by exploring their architectural trade-offs. This work has the potential to significantly enhance large scale computation now used widely by researchers, the government and businesses in every sector of the economy. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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