PCI Express Gen6 FIR Filter Optimization by Space Mapping for Post-Silicon Validation

The evolution of PCI Express technology to Gen6, and the forthcoming Gen7, has markedly increased data transfer speeds, presenting new challenges for signal integrity. To tackle these challenges, advanced design strategies, such as enhanced equalization (EQ) techniques, are necessary. Traditional EQ methods typically involve extensive laboratory measurements, rendering the EQ process highly time intensive. In this paper, we introduce an optimization methodology for the PCIe Gen6 transmitter (Tx) equalizer utilizing the Aggressive Space Mapping (ASM) algorithm. Our ASM approach employs a computationally efficient surrogate as coarse model to estimate eye diagram margins. An implicit mapping between the coarse and fine model equalizer settings is established, leading to an efficient optimization for the EQ tuning process. The effectiveness of the ASM methodology is confirmed through simulations with the MATLAB SerDes Toolbox, resulting in notable enhancements in the eye diagram area and overall system margins.

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Published
2025-01-22
DOI
https://doi.org/10.1109/lamc63321.2025.10880559
Primary Topic
Iterative Learning Control Systems
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article
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article

PCI Express Gen6 FIR Filter Optimization by Space Mapping for Post-Silicon Validation

José E. Rayas‐Sánchez, Aurea E. Moreno-Mojica, Francisco E. Rangel-Patiño
Iterative Learning Control Systems
article

PCI Express Gen6 FIR Filter Optimization by Space Mapping for Post-Silicon Validation

José E. Rayas‐Sánchez, Aurea E. Moreno-Mojica, Francisco E. Rangel-Patiño
article en

Abstract

The evolution of PCI Express technology to Gen6, and the forthcoming Gen7, has markedly increased data transfer speeds, presenting new challenges for signal integrity. To tackle these challenges, advanced design strategies, such as enhanced equalization (EQ) techniques, are necessary. Traditional EQ methods typically involve extensive laboratory measurements, rendering the EQ process highly time intensive. In this paper, we introduce an optimization methodology for the PCIe Gen6 transmitter (Tx) equalizer utilizing the Aggressive Space Mapping (ASM) algorithm. Our ASM approach employs a computationally efficient surrogate as coarse model to estimate eye diagram margins. An implicit mapping between the coarse and fine model equalizer settings is established, leading to an efficient optimization for the EQ tuning process. The effectiveness of the ASM methodology is confirmed through simulations with the MATLAB SerDes Toolbox, resulting in notable enhancements in the eye diagram area and overall system margins.

Instituto Tecnológico y de Estudios Superiores de Occidente (MX), Universidad de Guadalajara (MX), Centro de Investigación y Proyectos en Ambiente y Desarrollo (MX)
Openalex Percentile: Top 97%
Iterative Learning Control Systems
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