[SKKU AI Colloqium2024] 김정래 교수-Native DRAM Cache: Re-architecting DRAM as a Large-Scale Cache for скачать в хорошем качестве

[SKKU AI Colloqium2024] 김정래 교수-Native DRAM Cache: Re-architecting DRAM as a Large-Scale Cache for

강연제목: Native DRAM Cache: Re-architecting DRAM as a Large-Scale Cache for Data Centers 강연자: 김정래 교수(성균관대학교) 강연요약: Contemporary data center CPUs are experiencing an unprecedented surge in core count. This trend necessitates scrutinized Last-Level Cache (LLC) strategies to accommodate increasing capacity demands. While DRAM offers significant capacity, using it as a cache poses challenges related to latency and energy. This talk introduces Native DRAM Cache (NDC), a novel DRAM architecture specifically designed to operate as a cache. NDC features innovative approaches, such as conducting tag matching and way selection within a DRAM subarray and repurposing existing precharge transistors for tag matching. These innovations facilitate Caching-In-Memory (CIM) and enable NDC to serve as a high-capacity LLC with high set-associativity, low-latency, high-throughput, and low-energy.