1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.AR2025★ 1 cited
FERMI-ML: A Flexible and Resource-Efficient Memory-In-Situ SRAM Macro for TinyML acceleration
Mukul Lokhande, Akash Sankhe, S. V. Jaya Chand +1
The growing demand for low-power and area-efficient TinyML inference on AIoT devices necessitates memory architectures that minimise data movement while sustaining high computation…
cs.AR2025
CORDIC Is All You Need
Omkar Kokane, Adam Teman, Anushka Jha +6
Artificial intelligence necessitates adaptable hardware accelerators for efficient high-throughput million operations. We present pipelined architecture with CORDIC block for linea…