Reducing run queue contention in shared memory multiprocessors

The performance of parallel processing systems, especially large systems, is sensitive to various types of overhead and contention. Performance consequences may be serious when contention occurs for hardware resources such as memory or the interconnection network. Contention can also occur for software resources such as critical data structures maintained by either system or application software. A run queue is one such critical data structure that can affect overall system performance. There are two basic types of run queues, centralized and distributed. Both present performance problems. There are also several techniques to mitigate their drawbacks, but none is completely satisfactory. Instead, the author proposes a different run queue organization, a hierarchical organization that inherits the best features of the centralized and the distributed queue organizations while avoiding their pitfalls. Thus, the hierarchical organization is suitable for building large-scale multiprocessor systems