Case Study 3: Managing Contention for Shared Resources on Multicore Processors D
ID: 3536834 • Letter: C
Question
Case Study 3: Managing Contention for Shared Resources on Multicore Processors
Due Week 8 and worth 100 points
Computer systems with multicore processors can increase performance by running applications in parallel, thus increasing the throughput that the computer system is able to attain. However, contention for caches, memory controllers, and interconnections may hinder performance and create deadlocks for resources. Read the paper %u201C Managing Contention for Shared Resources on Multicore Processors%u201D, located in Week 8 of the online course shell. This case study proposes using contention-aware scheduling algorithms to alleviate the contention problems.
Write a four to five (4-5) page paper in which you:
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The specific course learning outcomes associated with this assignment are:
Explanation / Answer
Finding an efficient schedule for a task graph on several processors is a trade-off between maximising concurrency and minimising interprocessor communication. Task duplication is a technique that has been employed to reduce or avoid interprocessor communication. Certain tasks are duplicated on several processors to produce the data locally and avoid the communication among processors. Most of the algorithms using task duplication have been proposed for the classic scheduling model, which allows concurrent communication and ignores contention for communication resources. It is increasingly recognised that this classic model is unrealistic and does not permit creating accurate and efficient schedules. The recently proposed contention model introduces contention awareness into task scheduling by assigning the edges of the task graph to the links of the communication network. It is intuitive that scheduling under such a model benefits even more from task duplication, yet no such algorithm has been proposed as it is not trivial to duplicate tasks under the contention model. This paper proposes a contention-aware task duplication scheduling algorithm. We investigate the fundamentals for task duplication in the contention model and propose an algorithm that is based on state-of-the-art techniques found in task duplication and contention-aware algorithms. An extensive experimental evaluation demonstrates the significant improvements to the speedup of the produced schedules.
Contention for shared resources on multicore processors remains an unsolved problem in existing systems despite significant research efforts dedicated to this problem in the past. Previous solutions focused primarily on hardware techniques and software page coloring to mitigate this problem. Our goal is to investigate how and to what extent contention for shared resource can be mitigated via thread scheduling. Scheduling is an attractive tool, because it does not require extra hardware and is relatively easy to integrate into the system. Our study is the first to provide a comprehensive analysis of contention-mitigating techniques that use only scheduling. The most difficult part of the problem is to find a classification scheme for threads, which would determine how they affect each other when competing for shared resources. We provide a comprehensive analysis of such classification schemes using a newly proposed methodology that enables to evaluate these schemes separately from the scheduling algorithm itself and to compare them to the optimal. As a result of this analysis we discovered a classification scheme that addresses not only contention for cache space, but contention for other shared resources, such as the memory controller, memory bus and prefetching hardware. To show the applicability of our analysis we design a new scheduling algorithm, which we prototype at user level, and demonstrate that it performs within 2% of the optimal. We also conclude that the highest impact of contention-aware scheduling techniques is not in improving performance of a workload as a whole but in improving quality of service or performance isolation for individual applications.
cheduling a task graph onto several processors is a trade-off between maximising concurrency and minimising interprocessor communication. A technique to reduce or avoid interprocessor communication is task duplication. Certain tasks are duplicated on several processors to produce the data locally and avoid the communication among processors. Most algorithms using task duplication are for the classic model, which allows concurrent communication and ignores contention for communication resources. The recently proposed, more realistic contention model introduces contention awareness into task scheduling by assigning the edges of the task graph to the links of the communication network. It is intuitive that scheduling under such a model benefits even more from task duplication. This paper proposes a contention-aware task duplication scheduling algorithm, after investigating how to use task duplication in the contention model. An extensive experimental evaluation demonstrates the significant improvements to the speedup of the produced schedules.