Streamlined cxl memory fabric with lightweight scalable provisioning

Abstract

Large-scale compute environments for Artificial Intelligence (AI) and High-Performance Computing (HPC) may utilize memory fabric infrastructures to achieve higher workload performance compared to conventional networking-only infrastructures. However, the role of memory fabrics extends beyond high-end use cases into general compute scenarios in public cloud, private cloud, and hybrid enterprise environments, where Memory-as-a-Service (Memory-aaS) augments and complements the portfolio of services provided to tenants in the datacenter. Embodiments herein disclose a streamlined CXL memory fabric utilizing a Resource Provisioning Unit (RPU), enabling lightweight, scalable provisioning of memory to CPUs, GPUs, and accelerators via CXL.io, CXL.mem, and CXL.cache. These embodiments support translation between asymmetric and symmetric memory transactions and operate in both switch-enabled CXL environments, such as CXL 2.0 and CXL 3.x, and non-switched CXL environments, such as CXL 1.1. The embodiments may further enable multi-tier memory pools and advanced protocol processing in switches, leveraging existing rack-level and pod-level topologies.