CXL-ClusterSim: Modeling CXL-Based Disaggregated Memory (arxiv.org)

CXL-ClusterSim is a new simulation framework designed to model CXL-based disaggregated memory clusters, developed using the gem5 simulator alongside the Structural Simulation Toolkit (SST). This advancement addresses significant challenges in modern computing, particularly in large-scale AI training and inference, where memory utilization is often inefficient. Disaggregated memory offers a solution to overprovisioning issues and reduces the high costs associated with DRAM in cloud computing environments. However, existing tools for simulating these systems have been limited, hindering the exploration of design and performance trade-offs. The introduction of CXL-ClusterSim is significant for the AI/ML community as it enables computer architects to delve into the design space of disaggregated memory more effectively. The framework's scalability and flexibility are designed to facilitate hardware/software co-design and performance optimization, potentially leading to more efficient and cost-effective computing systems for AI applications. By overcoming the limitations of previous simulation tools, CXL-ClusterSim could spark innovation in memory architecture, ultimately enhancing the efficacy of AI model training and inference processes.