Adil Mahmud Choudhury
Kamruddin Nur
ABSTRACT
For last few decades, multitasking is at its highest demand. To achieve multitasking, symmetric & asymmetric multi-core processors system is a popular technology. Asymmetric multi-core processors (AMPs) use the same instruction set architecture (ISA) but different clock frequency. It is shown that AMPs deliver better performance per watt comparing to its symmetric counterpart. The future multi-core system will combine a few fast cores & many slow cores. Fast core means high power consumption with complex pipelines and high clock frequency, where the slow core will have low power consumption with simple pipelines and low clock frequency. To get the best performance from the asymmetric multi-core processors, the best scheduling policy will play an important role. Scheduling co-running applications in the most suitable core types are very vital for AMPs to get its best performance. Various policies like contention-aware, parallelism-aware & asymmetric-aware need to be considered when developing a scheduling algorithm. For AMPs, contention for resource sharing is a key performance-limiting factor. Despite noteworthy research efforts, the contention for resource sharing in the multi-core processor remains unsolved. In this paper, we discuss the latest five contention-aware scheduling algorithms of AMPs. We present a comparative study exploiting the technique, parameter & performance improvement so that the future computer scientist can develop a contention-aware solution more precisely.
- Saeid Barati and Hank Hoffmann. 2016. Providing fairness in heterogeneous multicores with a predictive, adaptive scheduler. In 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE, 38--49.Google Scholar
Cross Ref
- Dhruba Chandra, Fei Guo, Seongbeom Kim, and Yan Solihin. 2005. Predicting inter-thread cache contention on a chip multi-processor architecture. In 11th International Symposium on High-Performance Computer Architecture. IEEE, 340--351.Google ScholarDigital Library
- Genti Daci and Megi Tartari. 2013. A comparative review of contention-aware scheduling algorithms to avoid contention in multicore systems. In Proceedings of the third international conference on trends in information, telecommunication and computing. Springer, 99--106.Google ScholarCross Ref
- Tanima Dey, Wei Wang, Jack Davidson, and Mary Lou Soffa. [n.d.]. A Study of the Effect of Prefetching in Shared-Memory Resource Contention. Memory 1, L1 ([n.d.]), L1.Google Scholar
- Jiun-Hung Ding, Ya-Ting Chang, Zhou-dong Guo, Kuan-Ching Li, and Yeh-Ching Chung. 2014. An efficient and comprehensive scheduler on Asymmetric Multicore Architecture systems. Journal of Systems Architecture 60, 3 (2014), 305--314.Google ScholarDigital Library
- Xiaokang Fan, Yulei Sui, and Jingling Xue. 2015. Contention-aware scheduling for asymmetric multicore processors. In 2015 IEEE 21st International Conference on Parallel and Distributed Systems (ICPADS). IEEE, 742--751.Google Scholar
- Alexandra Fedorova, Margo Seltzer, and Michael D Smith. 2007. Improving performance isolation on chip multiprocessors via an operating system scheduler. In 16th International Conference on Parallel Architecture and Compilation Techniques (PACT 2007). IEEE, 25--38.Google ScholarDigital Library
- Avner Friedman. 1992. Interprocessor memory contention. In Mathematics in Industrial Problems. Springer, 112--121.Google Scholar
- Adrian Garcia-Garcia, Juan Carlos Saez, and Manuel Prieto-Matias. 2017. Delivering Fairness on Asymmetric Multicore Systems via Contention-Aware Scheduling. In European Conference on Parallel Processing. Springer, 610--622.Google Scholar
- Muneeb Khan, Andreas Sandberg, and Erik Hagersten. 2014. A case for resource efficient prefetching in multicores. In 2014 43rd International Conference on Parallel Processing. IEEE, 101--110.Google ScholarDigital Library
- Rakesh Kumar, Keith I Farkas, Norman P Jouppi, Parthasarathy Ranganathan, and Dean M Tullsen. 2003. Single-ISA heterogeneous multi-core architectures: The potential for processor power reduction. In Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture. IEEE Computer Society, 81.Google ScholarDigital Library
- Rakesh Kumar, Dean M Tullsen, Parthasarathy Ranganathan, Norman P Jouppi, and Keith I Farkas. 2004. Single-ISA heterogeneous multi-core architectures for multithreaded workload performance. In Proceedings. 31st Annual International Symposium on Computer Architecture, 2004. IEEE, 64--75.Google ScholarCross Ref
- Nagesh B Lakshminarayana, Jaekyu Lee, and Hyesoon Kim. 2009. Age based scheduling for asymmetric multiprocessors. In Proceedings of the conference on high performance computing networking, storage and analysis. IEEE, 1--12.Google ScholarDigital Library
- Tong Li, Dan Baumberger, David A Koufaty, and Scott Hahn. 2007. Efficient operating system scheduling for performance-asymmetric multi-core architectures. In SC'07: Proceedings of the 2007 ACM/IEEE conference on Supercomputing. IEEE, 1--11.Google ScholarDigital Library
- Simone Libutti, Giuseppe Massari, and William Fornaciari. 2016. Co-scheduling tasks on multi-core heterogeneous systems: An energy-aware perspective. IET Computers & Digital Techniques 10, 2 (2016), 77--84.Google ScholarCross Ref
- Tipp Moseley, Joshua L Kihm, Daniel A Connors, and Dirk Grunwald. 2005. Methods for modeling resource contention on simultaneous multithreading processors. In 2005 International Conference on Computer Design. IEEE, 373--380.Google ScholarDigital Library
- Sergey Zhuravlev, Sergey Blagodurov, and Alexandra Fedorova. 2010. Addressing shared resource contention in multicore processors via scheduling. In ACM Sigplan Notices, Vol. 45. ACM, 129--142.Google ScholarDigital Library
Index Terms
- Qalitative Study of Contention-aware Scheduling Algorithm for Asymmetric Multicore Processors
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