Jinin So | Senior Director, Memory System Architect
Samsung
Jinin So is a Senior Director & System Architect at Samsung, responsible for developing advanced CXL products and technologies, including CMM-DC (Computing), CMM-B (Disaggregated Memory System), and SMDK (Software Stack for CXL Products). He has played a key role as the lead architect in developing multiple groundbreaking technologies, such as the world's first CXL Process Near Memory Platform (CMM-DC), CXL Memory Expander (CMM-D), and DDR-based Near Memory Process DIMM (AXDIMM) at Samsung. Jinin has excellent knowledge of computer architecture, particularly in CPU/GPU/NPU with memory subsystems, and has in-depth expertise in Intel/AMD server system configurations and memory configurations for high-performance servers. With over 10 years of experience in memory module design, system-level SI/PI/thermal analysis, and five years in Process Near Memory System Architecture design, Jinin has contributed to defining memory module product specifications within JEDEC. He holds more than 10 U.S. patents and has authored over 10 publications.
Appearances:
Future of Memory and Storage - Day 3 @ 13:45
The Resurgence of CXL in the Al Era: How CXL Redefines High-Performance and Energy Efficient Al Inference with PNM technology
A few years ago, some industry report prematurely claimed that CXL was "dead" in the AI era, primarily citing its bandwidth limitations compared to ethernet based interconnect as like NVLink. However, such assessments were narrowly focused on single-turn LLM inference, specifically the decoding stage. In the current landscape of Agentic AI—driven by Reasoning, RAG (Retrieval-Augmented Generation), and Multi-Modal LLMs—the industry is witnessing an explosive growth in KV cache and an urgent need for its efficient storage and sharing.
CXL is now emerging as a critical solution, leveraging its low-latency characteristics alongside large-capacity memory pooling and sharing technologies. This presentation explores how CXL memory enhances the performance of Agentic AI inference. Furthermore, we will introduce additional performance gains and energy efficiency achieved through Process Near Memory (PNM) technologies. Finally, we will share Samsung’s latest System & SW innovations and empirical evaluation results that demonstrate the future of CXL-based AI infrastructure.
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