Friday, August 9, 2019
Managing Contention for Shared Resources on Multicore Processors Case Study
Managing Contention for Shared Resources on Multicore Processors - Case Study Example The advantages of parallel computing include saving on the time required for computing and providing concurrency where the multiple processors can solve several computational problems simultaneously. The modern computer systems with multicore processors apply the concept of parallel computing in their operation. In parallel computing, the computer systems share several hardware resources such as LLC and memory controllers to enhance their operation. Several processors cores are assigned to a common memory resource. Processors operating under the same memory resource may compete for the shared memory resource thus, causing traffic and congestions. This is referred to as contention. Contention causes slowing down of the computer system thus reducing the performance of the system (Yuejian, 2012). There are two types of contentions namely; communication contention and memory contention. Communication contention occurs when several processor cores contend for a common communication link. This causes traffic and performance degradation, and in turn slows performance. Memory contention on the other hand, occurs when several processors compete for resources from the same memory module. In a test to demonstrate how contention for the shared resources affects the operation of the computer system, three applications namely Soplex, Sphinx, and Namd were run simultaneously on an Intel quad core xeon system. Soplex, Sphinx, and Namd were paired to run in the same memory domain in different schedules. The result of the combinations of applications indicated a dramatic difference between the different pairs of applications. The applications run as a whole performed 20 percent better with the best schedule, while by running Soplex and Sphinx applications simultaneously the performance was great as 50 percent. The Soplex and Sphinx pair of combination sharing the same memory module was considered as the best schedule. The
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