Intellectual Property India Publishes Patent Application for 'Ultra Miniature Reconfigurable Fpga Architecture For Dynamic Hardware Optimization' Filed by Dr. Priyadharshlni Ramu R; Ahila D L; Satheesh Kumar S; Thilagavathi G; Jeba Sundari Ponvathi S; Kanimozhi L; Anjugam K; and Rubesh Ram M

MUMBAI, India, Jan. 23 -- Intellectual Property India has published a patent application (202541117204 A) filed by Dr. Priyadharshlni Ramu R; Ahila D L; Satheesh Kumar S; Thilagavathi G; Jeba Sundari Ponvathi S; Kanimozhi L; Anjugam K; and Rubesh Ram M, Chennai, Tamil Nadu, on Nov. 26, 2025, for 'ultra miniature reconfigurable fpga architecture for dynamic hardware optimization.'

Inventor(s) include Dr. Priyadharshlni Ramu R; Ahila D L; Satheesh Kumar S; Thilagavathi G; Jeba Sundari Ponvathi S; Kanimozhi L; Anjugam K; and Rubesh Ram M.

The application for the patent was published on Jan. 23, under issue no. 04/2026.

According to the abstract released by the Intellectual Property India: "ive rapid evolution of edge computing and embedded systems will require the development of hardware platforms that can deliver high performance under extreme constraints of size, energy, and cost. This invention describes an ultra-miniature reconfigurable FPGA architecture that enables real-time dynamic hardware optimization. Contrasting with traditional FPGA devices relying on resource-intensive configuration fabrics, the proposed architecture integrates lightweight configuration cells with adaptive logic blocks and a hierarchical routing network optimized for space-efficient implementation. A dynamic reconfiguration engine continuously monitors application workloads and autonomously reallocates logic resources to optimize processing efficiency at minimum power overhead. The architecture provides partial and runtime reconfiguration, enabling seamless functionality upgrades and fault recovery with no interruption to the system, its compact footprint makes It a perfect match for next-generation wearables, biomedical implants, the Internet of Things nodes, autonomous drones, and space-limited industrial systems. As such, it collocates high-performance, computing with extreme miniaturization and intelligent reconfiguration capability-a key design challenge facing emergent edge intelligence platforms. Computation density, energy efficiency, and operational adaptiveness are substantially improved, placing the technology as one of the transformational solutions for future adaptive hardware-embedded applications."

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