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On Advanced Methodologies for Microarchitecture Design Space Exploration

Published: 12 June 2024 Publication History

Abstract

With the ever-increasing complexity of microprocessors, microarchitectural design becomes over-challenging. Design space exploration (DSE) of microarchitecture configurations to obtain high-quality designs with different PPA trade-offs is time-consuming, due to the huge configuration space and inefficient VLSI verification flow. Many DSE frameworks proposed in previous works failed to systematically analyze the contribution of each algorithmic component to the full flow. This paper provides a novel methodology for designing DSE frameworks by separating DSE flow into stages, and discussing algorithmic instantiations in each stage with theoretical and experimental analyses. Newly formulated DSE frameworks guided by this methodology achieve state-of-the-art results in ICCAD’22 DSE contest evaluation environments.

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Dandan Li 2016. Efficient design space exploration via statistical sampling and AdaBoost learning. In Proc. DAC.
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cover image ACM Conferences
GLSVLSI '24: Proceedings of the Great Lakes Symposium on VLSI 2024
June 2024
797 pages
ISBN:9798400706059
DOI:10.1145/3649476
This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

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Published: 12 June 2024

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GLSVLSI '24
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GLSVLSI '24: Great Lakes Symposium on VLSI 2024
June 12 - 14, 2024
FL, Clearwater, USA

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Overall Acceptance Rate 312 of 1,156 submissions, 27%

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