HIERARCHICAL-CLUSTERING - A STRUCTURE FOR SCALABLE MULTIPROCESSOR OPERATING SYSTEM-DESIGN

We introduce the concept of hierarchical clustering as a way to structure shared-memory multiprocessor operating systems for scalability. The concept is based on clustering and hierarchical system design. Hierarchical clustering leads to a modular system, composed of easy-to-design and efficient building blocks. The resulting structure is scalable because it 1) maximizes locality, which is key to good performance in NUMA (non-uniform memory access) systems and 2) provides for concurrency that increases linearly with the number of processors. At the same time, there is tight coupling within a cluster, so the system performs well for local interactions that are expected to constitute the common case. A clustered system can easily be adapted to different hardware configurations and architectures by changing the size of the clusters. We show how this structuring technique is applied to the design of a microkernel-based operating system called HURRICANE. This prototype system is the first complete and running implementation of its kind and demonstrates the feasibility of a hierarchically clustered system. We present performance results based on the prototype, demonstrating the characteristics and behavior of a clustered system. In particular, we show how clustering trades off the efficiencies of tight coupling for the advantages of replication, increased locality, and decreased lock contention.