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- W4223950399 abstract "The very first Design Automation Conference was held in 1964 when computers were programmed with punch cards. The initial topics were related to automated Printed Circuit Board design, cell placement, and early attempts at transient circuit analysis. The next decades saw the introduction of key graph algorithms and numerical analysis methods. Optimal algorithms and more practical heuristic methods were published. The 1980ies saw the advent of simulated annealing, a universal heuristic optimization method that found many applications. The next decade introduced powerful numerical placement methods for millions of cells. Soon after, physical synthesis was born by combining several incremental synthesis and analysis tools. Today's commercial EDA tools run a very complex design flow that chains together hundreds of algorithms that were developed over 60 decades. Most effort is in the careful fine-tuning of parameters and addressing the complex - and often surprising - algorithmic interactions. This is a difficult trial-and-error process, driven by a small set of benchmarks. Machine Learning methods will take some of the human tuning efforts out of this loop. Some have already found their way in commercial tools. It will take a while before a Machine Learning method fully replaces a 'traditional' EDA algorithm. Each method in the flow has a limited sweet spot and is often run-time critical. On the other hand, conventional algorithms leave only insignificant opportunities for speed up through parallelism. Machine Learning methods may provide the only viable way to unlock the potential of massive cloud computing resources." @default.
- W4223950399 created "2022-04-19" @default.
- W4223950399 creator A5020251935 @default.
- W4223950399 date "2022-04-13" @default.
- W4223950399 modified "2023-09-27" @default.
- W4223950399 title "From Hard-Coded Heuristics to ML-Driven Optimization" @default.
- W4223950399 cites W3012493694 @default.
- W4223950399 doi "https://doi.org/10.1145/3505170.3511799" @default.
- W4223950399 hasPublicationYear "2022" @default.
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