Affiliation:
1. Rutgers University, Piscataway, NJ, USA
Abstract
Processors and operating systems (OSes) support multiple memory page sizes. Superpages increase Translation Lookaside Buffer (TLB) hits, while small pages provide fine-grained memory protection. Ideally, TLBs should perform well for any distribution of page sizes. In reality, set-associative TLBs -- used frequently for their energy efficiency compared to fully-associative TLBs -- cannot (easily) support multiple page sizes concurrently. Instead, commercial systems typically implement separate set-associative TLBs for different page sizes. This means that when superpages are allocated aggressively, TLB misses may, counter intuitively, increase even if entries for small pages remain unused (and vice-versa). We invent MIX TLBs, energy-frugal set-associative structures that concurrently support all page sizes by exploiting superpage allocation patterns. MIX TLBs boost the performance (often by 10-30%) of big-memory applications on native CPUs, virtualized CPUs, and GPUs. MIX TLBs are simple and require no OS or program changes.
Funder
Google
VMWare
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
Cited by
4 articles.
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1. Athena;Proceedings of the International Conference on Parallel Architectures and Compilation Techniques;2022-10-08
2. Improving Address Translation in Multi-GPUs via Sharing and Spilling aware TLB Design;MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture;2021-10-17
3. Morrigan: A Composite Instruction TLB Prefetcher;MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture;2021-10-17
4. Trident: Harnessing Architectural Resources for All Page Sizes in x86 Processors;MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture;2021-10-17