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COTSon: infrastructure for full system simulation

Authors:

Eduardo Argollo,

Paolo Faraboschi,

Matteo Monchiero,

Daniel OrtegaAuthors Info & Claims

ACM SIGOPS Operating Systems Review, Volume 43, Issue 1

Pages 52 - 61

https://doi.org/10.1145/1496909.1496921

Published: 01 January 2009 Publication History

Abstract

Simulation has historically been the primary technique used for evaluating the performance of new proposals in computer architecture. Speed and complexity considerations have traditionally limited its applicability to single-thread processors running application-level code. This is no longer sufficient to model modern multicore systems running the complex workloads of commercial interest today.

COTSon is a simulator framework jointly developed by HP Labs and AMD. The goal of COTSon is to provide fast and accurate evaluation of current and future computing systems, covering the full software stack and complete hardware models. It targets cluster-level systems composed of hundreds of commodity multicore nodes and their associated devices connected through a standard communication network. COTSon adopts a functional-directed philosophy, where fast functional emulators and timing models cooperate to improve the simulation accuracy at a speed sufficient to simulate the full stack of applications, middleware and OSs.

This paper describes the changes in simulation philosophy we embraced in COTSon to address these new challenges. We base functional emulation on established, fast and validated tools that support commodity OSs and complex multitier applications. Through a robust interface between the functional and timing domain, we can leverage other existing simulators for individual sub-components, such as disks or networks. We abandon the idea of "always-on" cycle-based simulation in favor of statistical sampling approaches that can trade accuracy for speed.

COTSon opens up a new dimension in the speed/accuracy space, allowing simulation of a cluster of nodes several orders of magnitude faster with a minimal accuracy loss.

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Cited By

Hwang ILee JKang HLee GKim H(2025)Survey of CPU and memory simulators in computer architecture: A comprehensive analysis including compiler integration and emerging technology applicationsSimulation Modelling Practice and Theory10.1016/j.simpat.2024.103032138(103032)Online publication date: Jan-2025
https://doi.org/10.1016/j.simpat.2024.103032
Liu CSabu AChaudhari AKang QCarlson T(2024)Pac-Sim: Simulation of Multi-threaded Workloads using Intelligent, Live SamplingACM Transactions on Architecture and Code Optimization10.1145/368054821:4(1-26)Online publication date: 20-Nov-2024
https://dl.acm.org/doi/10.1145/3680548
Åleskog CGrahn HBorg A(2024)A Comparative Study on Simulation Frameworks for AI Accelerator Evaluation2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW63119.2024.00073(321-328)Online publication date: 27-May-2024
https://doi.org/10.1109/IPDPSW63119.2024.00073
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Index Terms

COTSon: infrastructure for full system simulation
1. Hardware
  1. Hardware validation

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Published In

cover image ACM SIGOPS Operating Systems Review

ACM SIGOPS Operating Systems Review Volume 43, Issue 1

January 2009

97 pages

ISSN:0163-5980

DOI:10.1145/1496909

Issue’s Table of Contents

Copyright © 2009 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 January 2009

Published in SIGOPS Volume 43, Issue 1

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Cited By

Hwang ILee JKang HLee GKim H(2025)Survey of CPU and memory simulators in computer architecture: A comprehensive analysis including compiler integration and emerging technology applicationsSimulation Modelling Practice and Theory10.1016/j.simpat.2024.103032138(103032)Online publication date: Jan-2025
https://doi.org/10.1016/j.simpat.2024.103032
Liu CSabu AChaudhari AKang QCarlson T(2024)Pac-Sim: Simulation of Multi-threaded Workloads using Intelligent, Live SamplingACM Transactions on Architecture and Code Optimization10.1145/368054821:4(1-26)Online publication date: 20-Nov-2024
https://dl.acm.org/doi/10.1145/3680548
Åleskog CGrahn HBorg A(2024)A Comparative Study on Simulation Frameworks for AI Accelerator Evaluation2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW63119.2024.00073(321-328)Online publication date: 27-May-2024
https://doi.org/10.1109/IPDPSW63119.2024.00073
Sabu ALiu CCarlson T(2024)Viper: Utilizing Hierarchical Program Structure to Accelerate Multi-Core SimulationIEEE Access10.1109/ACCESS.2024.335406912(17669-17678)Online publication date: 2024
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Lee JMin DByun IJang HKim J(2023)Fast, Light-weight, and Accurate Performance Evaluation using Representative Datacenter BehaviorsProceedings of the 24th International Middleware Conference10.1145/3590140.3629117(220-233)Online publication date: 27-Nov-2023
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Eyerman SSteen SHeirman WHur I(2023)Simulating Wrong-Path Instructions in Decoupled Functional-First Simulation2023 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)10.1109/ISPASS57527.2023.00021(124-133)Online publication date: Apr-2023
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Ortiz JCorbalan-Navarro DAragon JGonzalez A(2022)MEGsim: A Novel Methodology for Efficient Simulation of Graphics Workloads in GPUs2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)10.1109/ISPASS55109.2022.00007(69-78)Online publication date: May-2022
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