CHAMP: A Configurable, Hot-Swappable Edge Architecture for Adaptive Biometric Tasks
Joel Brogan, Matthew Yohe, David Cornett

TL;DR
CHAMP is a modular, configurable edge AI platform enabling rapid swapping of biometric and AI modules for flexible, high-performance field applications, with demonstrated near-linear scaling and secure data handling.
Contribution
This paper introduces CHAMP, a novel plug-and-play edge architecture with FPGA accelerators and a custom OS, allowing dynamic reconfiguration and secure biometric data management.
Findings
Near-linear throughput scaling with multiple accelerators
Effective modular design for diverse biometric tasks
Secure cryptographic data handling capabilities
Abstract
What if you could piece together your own custom biometrics and AI analysis system, a bit like LEGO blocks? We aim to bring that technology to field operators in the field who require flexible, high-performance edge AI system that can be adapted on a moment's notice. This paper introduces CHAMP (Configurable Hot-swappable Architecture for Machine Perception), a modular edge computing platform that allows operators to dynamically swap in specialized AI "capability cartridges" for tasks like face recognition, object tracking, and document analysis. CHAMP leverages low-power FPGA-based accelerators on a high-throughput bus, orchestrated by a custom operating system (VDiSK) to enable plug-and-play AI pipelines and cryptographically secured biometric datasets. In this paper we describe the CHAMP design, including its modular scaling with multiple accelerators and the VDiSK operating system…
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Taxonomy
TopicsUser Authentication and Security Systems
