Artificial Intelligence Memory Posted on : Jul 16 - 2019

At the 2019 Semicon Conference Applied Materials (AMAT) had a day-long seminar focused on technology, particularly memory, for artificial intelligence (AI) applications. In addition to talks by AI experts, the company also talked about their tools for manufacturing magnetic random access memory (MRAM) as well as resistive random access memory (RRAM) and Phase Change Memory (PCM).  We will talk about a workshop at Stanford in August will explore emerging memories enabling artificial intelligence, especially for embedded products, such as IoT devices.

Gary Dickerson from Applied Materials gave a kick-off talk at the seminar. He talked about the growth of data and the importance of memory to support data centers as well as the edge. Increasing performance requirements will require improved throughput and latency for AI training in data centers (the Cloud) as well as inference engines in data centers and at the edge of networks.

MRAM, with its high performance and greater density potential than SRAM and other memory technologies, such as NOR flash, will be a key enabler of future edge inference technologies enabling sophisticated IoT devices and applications.  RRAM and PCM will find their greatest applications in data centers.  In particular, RRAM and PCM technology may be used in neuromorphic computing applications running sophisticated AI algorithms.

The image below shows Applied Material’s Endura Clover MRAM Physical Vapor Deposition (PVD) platform that can deposit the multi-level structures in STT-MRAM memory devices without going out of vacuum.  The company also was showing their Endura Impulse PVD System for PCM and RRAM. View More