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BigPower: Hierarchical Source-Level Module Power Estimati...
[Submitted on 11 Jun 2026] · 2026-06-15 · via cs updates on arXiv.org

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Abstract:Accurate power estimation is important for understanding and optimizing CPU power behavior, yet practical workflows often rely on simulation-derived information or post-silicon analysis. In this work, we present BigPower, a hierarchical source-level surrogate model for fine-grained module-level power estimation during CPU design. BigPower leverages large language model-based representations together with architectural hierarchy, module connectivity, configuration parameters, and workload context to estimate module-level power consumption directly from source-level design information, without requiring additional simulation during inference. Experimental results in the open-source XiangShan processor family demonstrate practical fine-grained power estimation across diverse configurations and workloads, offering an efficient alternative to conventional simulation-based workflows.

Submission history

From: Honghua Zhu [view email]
[v1] Thu, 11 Jun 2026 15:05:13 UTC (396 KB)