Scale-Model Simulation

Computer architects extensively use simulation to steer future processor research and development. Simulating large-scale multicore processors is extremely time-consuming and is sometimes impossible because of simulation infrastructure limitations. This paper proposes scale-model simulation, a novel...

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Bibliographic Details
Published inIEEE computer architecture letters Vol. 20; no. 2; pp. 175 - 178
Main Authors Liu, Wenjie, Heirman, Wim, Eyerman, Stijn, Akram, Shoaib, Eeckhout, Lieven
Format Journal Article
LanguageEnglish
Published New York IEEE 01.07.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Bibliographies
Machine learning
Microprocessors
multi-core system simulation
Operating systems
Performance prediction
R&D
Research & development
Scale models
Simulation
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Summary:Computer architects extensively use simulation to steer future processor research and development. Simulating large-scale multicore processors is extremely time-consuming and is sometimes impossible because of simulation infrastructure limitations. This paper proposes scale-model simulation, a novel methodology to predict large-scale multicore system performance. Scale-model simulation first constructs and simulates a scale model of the target system with reduced core count and shared resources. Target system performance is then predicted through machine-learning (ML) based extrapolation. Scale-model simulation predicts 32-core target system performance based on a single-core scale model with an average error of 8.0% and 15.8% for homogeneous and heterogeneous workloads, respectively, while yielding a 28× simulation speedup.
ISSN:1556-6056
1556-6064
DOI:10.1109/LCA.2021.3133112