MedusaVM: Decentralizing virtual memory system for multithreaded applications on many-core

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Abstract

Virtual memory system multiplexes the single physical memory for multiple running processes with two centralized resources, i.e., virtual memory space and page table hierarchy. However, for multithreaded applications running a single address space, current centralized VM system design encounters severe scalability bottlenecks and significantly impedes the application speedup increment on many-core systems. This paper proposes a novel VM system called MedusaVM to scale VM system to many cores. To this end, MedusaVM partitions the global virtual memory space and page table tree in a memory-efficient way, eliminating performance interference and lock contention between cores. Moreover, MedusaVM also provides a traditional shared memory interface for multithreaded applications. Our prototype system is implemented based on Linux kernel 4.4.0 and glibc 2.23. Experimental results evaluated on a 32-core machine demonstrate that MedusaVM scales much better than Linux kernel and uses 22 × less memory compared with the state-of-art approach. For microbenchmarks experiments, MedusaVM achieves nearly linear performance speedup. In multithreaded applications Metis and Psearchy, MedusaVM also significantly outperforms Linux kernel by up to a factor of 2.5 ×.

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APA

Cai, M., Liu, S., Yang, W., & Huang, H. (2018). MedusaVM: Decentralizing virtual memory system for multithreaded applications on many-core. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11334 LNCS, pp. 267–283). Springer Verlag. https://doi.org/10.1007/978-3-030-05051-1_19

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