Lune

ASPLOS2025顶会

Virtuoso: Enabling Fast and Accurate Virtual Memory Research via an Imitation-based Operating System Simulation Methodology

Konstantinos Kanellopoulos, Konstantinos Sgouras, F. Nisa Bostanci, Andreas Kosmas Kakolyris, Berkin Kerim Konar, Rahul Bera, Mohammad Sadrosadati, Rakesh Kumar, Nandita Vijaykumar, Onur Mutlu

2025年份
8被引次数
3顶会引用

摘要

The unprecedented growth in data demand from emerging applications has turned virtual memory (VM) into a major performance bottleneck. VM's overheads are expected to persist as memory requirements continue to increase. Researchers explore new hardware/OS co-designs to optimize VM across diverse applications and systems. To evaluate such designs, researchers rely on various simulation methodologies to model VM components. Unfortunately, current simulation tools (i) either lack the desired accuracy in modeling VM's software components or (ii) are too slow and complex to prototype and evaluate schemes that span across the hardware/software boundary.

We introduce Virtuoso, a new simulation framework that enables quick and accurate prototyping and evaluation of the software and hardware components of the VM subsystem.

The key idea of Virtuoso is to employ a lightweight userspace OS kernel, called MimicOS, that (i) accelerates simulation time by imitating only the desired kernel functionalities, (ii) facilitates the development of new OS routines that imitate real ones, using an accessible high-level programming interface, (iii) enables accurate and flexible evaluation of the application-and system-level implications of VM after integrating Virtuoso to a desired architectural simulator.

In this work, we integrate Virtuoso into five diverse architectural simulators, each specializing in different aspects of system design, and heavily enrich it with multiple stateof-the-art VM schemes. This way, we establish a common ground for researchers to evaluate current VM designs and to develop and test new ones. We demonstrate Virtuoso's flexibility and versatility by evaluating five diverse use cases, yielding new insights into state-of-the-art VM techniques. Our validation shows that Virtuoso ported on top of Sniper, a state-of-the-art microarchitectural simulator, models (i) the memory management unit of a real high-end server-grade CPU with 82% accuracy, and (ii) the page fault latency of a real Linux kernel with up to 79% accuracy. Consequently, Virtuoso models the IPC performance of a real high-end servergrade CPU with 21% higher accuracy than the baseline version of Sniper. Virtuoso's accuracy benefits incur an average simulation time overhead of only 20%, on top of four baseline architectural simulators. The source code of Virtuoso is freely available at https://github.com/CMU-SAFARI/Virtuoso.

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper3

问问它们各自怎么用它

它引用的顶会 Paper44

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖