Victima: Drastically Increasing Address Translation Reach by Leveraging Underutilized Cache Resources
Konstantinos Kanellopoulos, Hong Chul Nam, Nisa Bostanci, Rahul Bera, Mohammad Sadrosadati, Rakesh Kumar, Davide Basilio Bartolini, Onur Mutlu
摘要
Address translation is a performance bottleneck in data-intensive workloads due to large datasets and irregular access patterns that lead to frequent high-latency page table walks (PTWs). PTWs can be reduced by using (i) large hardware TLBs or (ii) large softwaremanaged TLBs. Unfortunately, both solutions have significant drawbacks: increased access latency, power and area (for hardware TLBs), and costly memory accesses, the need for large contiguous memory blocks, and complex OS modifications (for software-managed TLBs).
We present Victima, a new software-transparent mechanism that drastically increases the translation reach of the processor by leveraging the underutilized resources of the cache hierarchy. The key idea of Victima is to repurpose L2 cache blocks to store clusters of TLB entries, thereby providing an additional low-latency and high-capacity component that backs up the last-level TLB and thus reduces PTWs. Victima has two main components. First, a PTW cost predictor (PTW-CP) identifies costly-to-translate addresses based on the frequency and cost of the PTWs they lead to. Leveraging the PTW-CP, Victima uses the valuable cache space only for TLB entries that correspond to costly-to-translate pages, reducing the impact on cached application data. Second, a TLB-aware cache replacement policy prioritizes keeping TLB entries in the cache hierarchy by considering (i) the translation pressure (e.g., last-level TLB miss rate) and (ii) the reuse characteristics of the TLB entries.
Our evaluation results show that in native (virtualized) execution environments Victima improves average end-to-end application performance by 7.4% (28.7%) over the baseline four-level radix-treebased page table design and by 6.2% (20.1%) over a state-of-the-art software-managed TLB, across 11 diverse data-intensive workloads. Victima delivers similar performance as a system that employs an optimistic 128K-entry L2 TLB, while avoiding the associated area and power overheads. Victima (i) is effective in both native and virtualized environments, (ii) is completely transparent to application and system software, (iii) unlike large software-managed TLBs, does not require contiguous physical allocations, (iv) is compatible with modern large page mechanisms and (iv) incurs very small area and power overheads of 0.04% and 0.08%, respectively, on a modern high-end CPU. The source code of Victima is freely available at https://github.com/CMU-SAFARI/Victima.
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引用它的顶会 Paper7
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- A Case for Speculative Address Translation with Rapid Validation for GPUsJunhyeok Park, Osang Kwon, Yongho Lee, Seongwook Kim 等MICRO 2024 · 被引用 13 次
- Distributed Page Table: Harnessing Physical Memory as an Unbounded Hashed Page TableOsang Kwon, Yongho Lee, Junhyeok Park, Sungbin Jang 等MICRO 2024 · 被引用 7 次
- Instruction-Aware Cooperative TLB and Cache Replacement PoliciesDimitrios Chasapis, Georgios Vavouliotis, Daniel A. Jiménez, Marc CasasASPLOS 2025 · 被引用 5 次
- Revelator: Rapid Data Fetching Via System-Software-Guided Hash-Based Speculative Address TranslationKonstantinos Kanellopoulos, Konstantinos Sgouras, Harsh Songara, Andreas Kosmas Kakolyris 等ISCA 2026
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- Perforated Page: Supporting Fragmented Memory Allocation for Large PagesChang Hyun Park, Sanghoon Cha, Bokyeong Kim, Youngjin Kwon 等ISCA 2020 · 被引用 35 次
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