BROWSE
Detail
Journal Article
인공지능 반도체 메모리 기술 동향
- Issue Date
- 2024-10
- Citation
- 전자통신동향분석, v.39, no.5, pp.21-30
- ISSN
- 1225-6455
- Publisher
- 한국전자통신연구원
- Language
- Korean
- Type
- Journal Article
- Abstract
- Memory can refer to a storage device that collects data, and it has evolved to increase the reading/writing speed and reduce the power consumption. As large amounts of data are processed by artificial intelligence services, the memory data capacity requires expansion. Dynamic random-access memory (DRAM) is the most widely used type of memory. In particular, graphics double date rate and high-bandwidth memory allow to quickly transfer large amounts of data and are used as memory solutions for artificial intelligence semiconductors. We analyze development trends in DRAM from the perspectives of processing speed and power consumption. We summarize the characteristics required for next-generation memory by comparing DRAM and other types of memory implementations. Moreover, we examine the shortcomings of DRAM and infer a next-generation memory for their compensation. We also describe the operating principles of spin-torque transfer magnetic random access memory, which may replace DRAM in next-generation devices, and explain its characteristics and advantages.
- KSP Keywords
- Data Capacity, Development trends, Double date rate, Dynamic random-access memory(DRAM), High-Bandwidth Memory, Magnetic random access memory, Next-generation, Power Consumption, Processing speed, Storage device, artificial intelligence
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
