Samsung Electronics markets PIM chips at Hot Chip 33

Samsung Electronics' newest memory chips designed to process data using AI [SAMSUNG ELECTRONICS]

Samsung Electronics will increase its range of memory chips capable of performing data processing functions, introducing some of the newest such products during the Hot Chips 33 conference on Tuesday.

The Hot Chips symposium has been held since 1989 and is normally held in California. This year, it is fully online.

The chief function of memory chips, like dynamic random access memory (DRAM), is to store data efficiently, but Samsung has tried to add processing functions to them, a feature that has traditionally been reserved for system chips, like central processing units.

Processing-in-memory (PIM) integrates the computing function on top of data storage using artificial intelligence.

“PIM-enabled High Bandwidth Memory (HBM-PIM) is the industry’s first AI-tailored memory solution being tested in customer AI-accelerator systems, demonstrating tremendous commercial potential,” said Kim Nam-sung, senior vice president of DRAM Product & Technology at Samsung Electronics.

“Through standardization of the technology, applications will become numerous, expanding into HBM3 for next-generation supercomputers and AI applications, and even into mobile memory for on-device AI as well as for memory modules used in data centers.”

Xilinx, a U.S. producer of logic devices, expressed expectations about collaboration with Samsung to develop the advanced memory chips.

“Xilinx has been collaborating with Samsung Electronics to enable high-performance solutions for data center, networking and real-time signal processing applications starting with the Virtex UltraScale+ HBM family, and recently introduced our new and exciting Versal HBM series products,” said Arun Varadarajan Rajagopal, senior director, Product Planning at Xilinx.

“We are delighted to continue this collaboration with Samsung as we help to evaluate HBM-PIM systems for their potential to achieve major performance and energy-efficiency gains in AI applications.”

BY PARK EUN-JEE [park.eunjee@joongang.co.kr]