System Margining Surrogate-Based Optimization in Post-Silicon Validation
| Autor: | Jose L. Chavez-Hurtado, Nagib Hakim, Andres Viveros-Wacher, Jose E. Rayas-Sanchez, Francisco E. Rangel-Patino |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Radiation
Computer science Design of experiments 020208 electrical & electronic engineering Process (computing) Physical layer Physical system 020206 networking & telecommunications 02 engineering and technology Post-silicon validation Condensed Matter Physics Data modeling Surrogate model PHY 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Simulation |
| Zdroj: | IEEE Transactions on Microwave Theory and Techniques. 65:3109-3115 |
| ISSN: | 1557-9670 0018-9480 |
| DOI: | 10.1109/tmtt.2017.2701368 |
| Popis: | There is an increasingly higher number of mixed-signal circuits within microprocessors. A significant portion of them corresponds to high-speed input/output (HSIO) links. Post-silicon validation of HSIO links is critical to provide a release qualification decision. One of the major challenges in HSIO electrical validation is the physical layer (PHY) tuning process, where equalization techniques are typically used to cancel any undesired effect. Current industrial practices for PHY tuning in HSIO links are very time-consuming, since they require massive laboratory measurements. On the other hand, surrogate modeling techniques allow to develop an approximation of a system response within a design space of interest. In this paper, we analyze several surrogate modeling methods and design of experiments techniques to identify the best approach to efficiently optimize a receiver equalizer. We evaluate the models performance by comparing with actual measured responses on a real server HSIO link. We then perform a surrogate-based optimization on the best model to obtain the optimal PHY tuning settings of an HSIO link. Our methodology is validated by measuring the real functional eye diagram of the physical system using the optimal surrogate model solution. |
| Databáze: | OpenAIRE |
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