CXL.mem and the resulting memory pool are promising and gaining great attention. Unlike local memory, CXL DIMMs stay at the I/O subsystem, whose inferior performance can easily impact the processor pipeline and memory subsystem, yielding performance interference, hardware contention, obscure behaviors, and underutilized communication and computing resources. However, our community lacks a tool to understand and profile the CXL.mem protocol execution end-to-end between CPU and remote DIMM.

SmartNICs have become an indispensable communication fabric and computing substrate in today’s data centers and enterprise clusters, providing in-network computing capabilities for traversed packets and benefiting a range of applications across the system stack. Building an efficient SmartNIC-assisted solution is generally non-trivial and tedious as it requires programmers to understand the SmartNIC architecture, refactor application logic to match the device’s capabilities and limitations, and correlate an application execution with traffic characteristics. A high-level SmartNIC performance model can decouple the underlying SmartNIC hardware device from its offloaded software implementations and execution contexts, thereby drastically simplifying and facilitating the development process. However, prior architectural models can hardly be applied due to their limited capabilities in dissecting the SmartNIC-offloaded program’s complexity, capturing the nondeterministic overlapping between computation and I/O, and perceiving diverse traffic profiles.

The recent emergence of low-power high-throughput programmable storage platforms-SmartNIC JBOF (just-a-bunch-of-flash)-motivates us to rethink the cluster architecture and system stack for energy-efficient large-scale data-intensive workloads. Unlike conventional systems that use an array of server JBOFs or embedded storage nodes, the introduction of SmartNIC JBOFs has drastically changed the cluster compute, memory, and I/O configurations. Such an extremely imbalanced architecture makes prior system design philosophies and techniques either ineffective or invalid.

With the rapid development of wireless network technology and the demand for interconnection of mobile edge computing, the integration of heterogeneous wireless networks is becoming more and more urgent. At the same time, the increasing scarcity of spectrum resources also requires heterogeneous net-works to effectively improve the utilization of spectrum resources without affecting the use of different licensed spectrum resources. This paper proposed a multi-channel millimeter-wave (mmWave) MAC protocol for mobile self-organizing heterogeneous networks. The mmWave Mac uses a bulk access transmission scheme to improve throughput efficiency and reduce latency for heterogeneous networks. In addition, cognitive radio technology is also introduced into the mmWave Mac to enhance the utilization of spectrum resources. Finally, by comparing the simulation results with other protocol, it is verified that the mmWave MAC protocol has good performance in terms of delay, and throughput efficiency.