Pangaea v2 : CXL-Based Disaggregated Memory System Architecture for Cloud-Native Orchestration

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Authors: Han Deok Lee, Jehoon Park, Younghyun Lee, Junhyeok Im, Jinah Jung, Jinin So, Siamak Tavallaei, Taehoon Lee, Woo Taek Shim, Chin-Hua Chang, Jianping Jiang, Sungwook Ryu
+3 more Taeksang Song, Wonhwa Shin, Sangjoon Hwang
Cited by: 2
References: 9

Abstract

Today’s data centers suffer from CPU and memory resource stranding because they often over-provision resources when deploying servers for worst-case scenarios. This problem gives rise to a disaggregated system architecture allowing each type of resource to be allocated, utilized and freed separately as required. In particular, research on disaggregated memory systems over the past few years has focused primarily on achieving low remote memory access latency over Ethernet, which is known as the RDMA optimization approach.In this paper, we introduce a dynamic rack-scale disaggregated memory system architecture, so called Pangaea v2 using ASIC-CXL H/W and memory orchestration S/W designed to increase the memory utilization of worker nodes between containerized applications execution in a Kubernetes, a major process container platform in the data center. In our evaluation with in-memory database application, disaggregated CXL memory system shows significantly better throughput improved by up to 10.2x/6.7x and 99th tail latency reduced to 96%/93% compared to RDMA with RoCEv2/InfiniBand.

Fields of Study & Subjects

Cloud Computing and Resource Management Parallel Computing and Optimization Techniques Distributed systems and fault tolerance

Publication details

Journal / source
IEEE Transactions on Computers
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
75
Issue
4
Pages
1261–1275
Publication date
20 January 2026