Performance Verification of the AmpereOne CPU Core
Doa'a Al-Otoom, Nicholas Kelly, Aaron Lindsay, Agreen Ahmadi, Ananth Kumar, Anthony Faubert, Benjamin Chaffin, Bret Toll, Eric Wallace, Lucas Crowthers, Mark Charney, Michael Chin, Michael Spradling, Scott Witscher, Sriyash Caculo, Syed Fakhri, Vivek Kothapalli, William Freelove, Mahesh Madhav
Abstract
As process technology scaling slows, microarchitectural innovation has become the primary driver of performance gains, making pre-silicon Performance Verification (PV) more critical than ever. This paper presents the industrial-scale PV methodology applied across four generations of the AmpereOne custom CPU core, centered on the cycle-accurate correlation of the RTL design against a trace-driven performance model. The methodology integrates data-driven workload curation, a high-frequency daily regression system, and a unified event-stream framework for analysis. We demonstrate this methodology through case studies of the Branch Prediction Unit and L2 Prefetcher, highlighting a hierarchical strategy that first isolates individual units for focused correlation before proceeding to full-core verification. The results demonstrate that this disciplined, iterative process is indispensable for avoiding costly post-silicon bugs and ensuring complex processors meet their performance targets. We end with a look towards the future of PV in the microprocessor industry.
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