A 28-nm 64-kb 31.6-TFLOPS/W Digital-Domain Floating-Point-Computing-Unit and Double-Bit 6T-SRAM Computing-in-Memory Macro for Floating-Point CNNs https://sscs.ieee.org/wp-content/themes/movedo/images/empty/thumbnail.jpg 150 150 https://secure.gravatar.com/avatar/8935a7dcd6741d8e23d45bb15c1470a8?s=96&d=mm&r=g
Abstract:
With the rapid advancement of artificial intelligence (AI), computing-in-memory (CIM) structure is proposed to improve energy efficiency (EF). However, previous CIMs often rely on INT8 data types, which pose challenges when addressing more complex networks, larger datasets, and increasingly intricate tasks. This work presents a double-bit 6T static random-access memory (…