Abstract

Computer systems are rapidly changing. Over the next few years, we will see wide-scale deployment of dynamically-scheduled processors that can issue multiple instructions every clock cycle, execute instructions out of order, and overlap computation and cache misses. We also expect clock-rates to increase, caches to grow, and multiprocessors to replace uniprocessors. Using SimOS, a complete machine simulation environment, this paper explores the impact of the above architectural trends on operating system performance. We present results based on the execution of large and realistic workloads (program development, transaction processing, and engineering compute-server) running on the IRIX 5.3 operating system from Silicon Graphics Inc. Looking at uniprocessor trends, we find that disk I/O is the first-order bottleneck for workloads such as program development and transaction processing. Its importance continues to grow over time. Ignoring I/O, we find that the memory system is the key bottleneck, stalling the CPU for over 50 % of the execution time. Surprisingly, however, our results show that this stall fraction is unlikely to increase on future machines due to increased cache sizes and new latency hiding techniques in processors. We also find that the benefits of these architectural trends spread broadly across a majority of the important services provided by the operating system. We find the situation to be much worse for multiprocessors. Most operating systems services consume 30-70 % more time than their uniprocessor counterparts. A large fraction of the stalls are due to coherence misses caused by communication between processors. Because larger caches do not reduce coherence misses, the performance gap between uniprocessor and multiprocessor performance will increase unless operating system developers focus on kernel restructuring to reduce unnecessary communication. The paper presents a detailed decomposition of execution time (e.g., instruction execution time, memory stall time separately for instructions and data, synchronization time) for important kernel services in the three workloads.

Citations