Rank-DSE: Neural Pareto Comparator of Microarchitecture Design Space Exploration Article Swipe
Peng Xu
,
Su Zheng
,
Mingzi Wang
,
Ziyang Yu
,
Shixin Chen
,
Tinghuan Chen
,
Keren Zhu
,
Tsung-Yi Ho
,
Bei Yu
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1145/3747294
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1145/3747294
The complexity of microarchitecture design has surged due to the expanding design space and time-intensive verification processes. Existing regression-based machine learning methods struggle with inaccurate estimations because of limited training samples. To address these challenges, we propose Rank-DSE, a novel framework for microarchitecture design space exploration (DSE) that leverages a Neural Pareto Comparator (NPC) to directly model the comparative relationships between different architecture designs. Rank-DSE bypasses the inaccuracies of absolute PPA (performance, power, area) predictions by focusing on relative comparisons. The NPC computes the probability of one architecture dominating another and employs semi-supervised learning to reduce the reliance on labeled data. Additionally, a reinforcement-learning-based sampling scheme with an updating baseline Pareto set accelerates the exploration process. Experimental results on the ICCAD 2021 benchmark demonstrate that Rank-DSE achieves superior search quality and cost-efficiency compared to state-of-the-art methods. Specifically, Rank-DSE improves hypervolume by up to 7% while reducing exploration cost by 53.09% compared to cutting-edge approaches. These results highlight the advantages of Rank-DSE in terms of efficiency and effectiveness for microarchitecture DSE.
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- en
- Landing Page
- https://doi.org/10.1145/3747294
- OA Status
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- References
- 51
- Related Works
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- OpenAlex ID
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https://openalex.org/W4411976826Canonical identifier for this work in OpenAlex
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https://doi.org/10.1145/3747294Digital Object Identifier
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Rank-DSE: Neural Pareto Comparator of Microarchitecture Design Space ExplorationWork title
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articleOpenAlex work type
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enPrimary language
- Publication year
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2025Year of publication
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2025-07-03Full publication date if available
- Authors
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Peng Xu, Su Zheng, Mingzi Wang, Ziyang Yu, Shixin Chen, Tinghuan Chen, Keren Zhu, Tsung-Yi Ho, Bei YuList of authors in order
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https://doi.org/10.1145/3747294Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1145/3747294Direct OA link when available
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Computer science, Microarchitecture, Comparator, Rank (graph theory), Pareto principle, Space (punctuation), Parallel computing, Computer architecture, Artificial intelligence, Mathematical optimization, Mathematics, Operating system, Electrical engineering, Voltage, Engineering, CombinatoricsTop concepts (fields/topics) attached by OpenAlex
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10Other works algorithmically related by OpenAlex
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