Efficient Processor-in-Memory Chip Accelerates AI Inference - EE Times India

Imec and GlobalFoundries have demonstrated a processor-in-memory chip that can achieve energy efficiency up to 2900 TOPS/W, approximately two orders of magnitude above today's commercial processor-in-memory chips. The chip uses an established idea, analog computing, implemented in SRAM in GlobalFoundries' 22nm fully-depleted silicon-on-insulator (FD-SOI) process technology. Imec's analog in-memory compute (AiMC) will be available to GlobalFoundries customers as a feature that can be implemented on the company's 22FDX platform. Analog compute Analog compute, or processor-inmemory, is an established technique that is already used in commercial AI accelerator chips from startups Mythic, Syntiant, Gyrfalcon and others. Since a neural network model may have tens or hundreds of millions of weights, sending data back and forth between the memory and the processor is inefficient.