Managing Contention for Shared Resources on Multicore Processors Case Study

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Managing Contention

"Contention for shared resources significantly impedes the efficient operation of multicore processors" (Fedorova, 2009). The authors of "Managing Contention for Shared Resources on Multicore Processors" (Fedorova, 2009) found that shared cache contention as well as prefetching hardware and memory interconnects were all responsible for performance degradation. After implementing a pain, sensitivity and intensity, model to test applications, the authors discovered that high miss rate applications must be kept apart and not co-scheduled on the same domain (memory). Therefore, the management of how the applications were scheduled by the scheduler would mitigate the performance degradation of the cache lines and the applications on the processors.

The authors built a prototype scheduler, called Distributed Intensity Online (DIO) that distributes intensive (high latest level cache (LLC) miss rates) after measuring online miss rates of the application. With the execution of eight different workloads for testing, the DIO improved workload performance by 11% (Fedorova, 2009) with some applications showing 60-80% improvement with the worst case schedules. The prefetching hardware was the application that showed the most improvement under DIO. It also shows potential for ensuring QoS (quality of service) for critical applications with a means of ensuring the worst scheduling assignments are never used.

Another schedule that was used was the Power DI (Distributed Intensity) to test the power consumption.

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Power DI clusters incoming applications on as few machines as possible, except machines with memory intensive applications. The concept is the same on a single machine only it clusters the applications on as few memory domains as possible. The effectiveness differed with the number of memory intensive applications. The greater the number of memory intensive applications, the greater number of domains, or machines, that would end up getting used. So, the greater the number of memory intensive applications, the greater amount of power that was used. Power DI was able to adjust to the properties of the workload to minimize the power used.

The authors found the dominant cause of performance degradation is contention of shared resources of front-side bus, prefetching resources, and memory controller. Applications that issue many cache misses will occupy the memory controller and the front-line bus, which hurts other applications that use that hardware and the applications themselves. Cache contention stems from two or more threads running on the same domain (memory). The cache consists of lines allocated to hold thread memory as the threads issue cache requests.….....

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