“AI chips commonly employ SRAM memory as buffers for their reliability and speed, which contribute to high performance. However, SRAM is expensive and demands significant area and energy consumption.

A technical paper titled “An energy-efficient 10T SRAM in-memory computing macro for artificial intelligence edge processor” was published by researchers at Atal Bihari Vajpayee-Indian Institute of ...

Memory has become an increasingly vital ingredient of the ultra-low-power Internet of Things (IoT) chip designs, and that’s apparent from Nordic Semiconductor’s acquisition of low-voltage embedded ...

NUREMBERG, Germany, March 14, 2017 (GLOBE NEWSWIRE) -- (Embedded World 2017) – NXP Semiconductors N.V. (NASDAQ:NXPI) announced today its new Kinetis K27/K28 family of ARM® Cortex®-M4-based ...