PS-TLB

Author:

Li Yong1,Melhem Rami1,Jones Alex K.1

Affiliation:

1. University of Pittsburgh, Pittsburgh, PA

Abstract

Traversing the page table during virtual to physical address translation causes pipeline stalls when misses occur in the translation-lookaside buffer (TLB). State-of-the-art translation proposals typically optimize a single aspect of translation performance (e.g., translation sharing, context switch performance, etc.) with potential trade-offs of additional hardware complexity, increased translation latency, or reduced scalability. In this article, we propose the partial sharing TLB (PS-TLB), a fast and scalable solution that reduces off-chip translation misses without sacrificing the timing-critical requirement of on-chip translation. We introduce the partial sharing buffer (PSB) which leverages application page sharing characteristics using minimal additional hardware resources. Compared to the leading TLB proposal that leverages sharing, PS-TLB provides a more than 45% improvement in translation latency with a 9% application speedup while using fewer storage resources. In addition, the page classification and PS-TLB architecture provide further optimizations including an over 30% reduction of interprocessor interrupts for coherence, and reduced context switch misses with fewer resources compared with existing methods.

Funder

Division of Computing and Communication Foundations

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Efficient Virtual Memory Sharing via On-Accelerator Page Table Walking in Heterogeneous Embedded SoCs;ACM Transactions on Embedded Computing Systems;2017-10-31

2. DTLB: Deterministic TLB for Tightly Bound Hard Real-Time Systems;2017 30th International Conference on VLSI Design and 2017 16th International Conference on Embedded Systems (VLSID);2017-01

3. A survey of techniques for architecting TLBs;Concurrency and Computation: Practice and Experience;2016-12-22

4. TokenTLB;Proceedings of the 2016 International Conference on Supercomputing;2016-06

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