Jitter Tolerance Acceleration Using the Golden Section Optimization Technique

Post-silicon validation of high-speed input/output (HSIO) links is a critical process for product qualification schedules of computer platforms under the current time-to-market (TTM) commitments. The goal of post-silicon validation for HSIO links is to confirm design robustness of both receiver (Rx) and transmitter (Tx) circuitry in a real application environment. One of the most common ways to evaluate the performance of a HSIO link is to characterize the Rx jitter tolerance (JTOL) performance by measuring the bit error rate (BER) through the link under worst stressing conditions. However, JTOL testing is very time-consuming when executing at specification BER, and the testing time is extremely increased when considering manufacturing process, voltage, and temperature (PVT) test coverage for a qualification decision. In order to speed up this process, we propose a new approach for JTOL testing based on the golden section algorithm. The proposed method takes advantage of the fast execution of the golden section search with a high BER, while overcoming the lack of correlation between different BERs by performing a downward linear search at the actual target BER until no errors are seen. Our proposed methodology is validated by implementing it in a server HSIO link

Fast jitter tolerance testing for high-speed serial links in post-silicon validation

Post-silicon electrical validation of high-speed input/output (HSIO) links is a critical process for product qualification schedules of high-performance computer platforms under current aggressive time-to-market (TTM) commitments. Improvements in signaling methods, circuits, and process technologies have allowed HSIO data rates to scale well beyond 10 Gb/s. Noise and EM effects can create multiple signal integrity problems, which are aggravated by continuously faster bus technologies. The goal of post-silicon validation for HSIO links is to ensure design robustness of both receiver (Rx) and transmitter (Tx) circuitry in real system environments. One of the most common ways to evaluate the performance of a HSIO link is to characterize the Rx jitter tolerance (JTOL) performance by measuring the bit error rate (BER) of the link under worst stressing conditions. However, JTOL testing is extremely time-consuming when executed at specification BER considering manufacturing process, voltage, and temperature (PVT) test coverage. In order to significantly accelerate this process, we propose a novel approach for JTOL testing based on an efficient direct search optimization methodology. Our approach exploits the fast execution of a modified golden section search with a high BER, while overcoming the lack of correlation between different BERs by performing a downward linear search at the actual target BER until no errors are found. Our proposed methodology is validated in a realistic industrial server post-silicon validation platform for three different computer HSIO links: SATA, USB3, and PCIe3.ITESO, A.C

A Holistic Formulation for System Margining and Jitter Tolerance Optimization in Industrial Post-Silicon Validation

There is an increasingly higher number of mixed-signal circuits within microprocessors and systems on chip (SoC). A significant portion of them corresponds to high-speed input/output (HSIO) links. Post-silicon validation of HSIO links can be critical for making a product release qualification decision under aggressive launch schedules. The optimization of receiver analog circuitry in modern HSIO links is a very time consuming post-silicon validation process. Current industrial practices are based on exhaustive enumeration methods to improve either the system margins or the jitter tolerance compliance test. In this paper, these two requirements are addressed in a holistic optimization-based approach. We propose a novel objective function based on these two metrics. Our method employs Kriging to build a surrogate model based on system margining and jitter tolerance measurements. The proposed method, tested with three different realistic server HSIO links, is able to deliver optimal system margins and guarantee jitter tolerance compliance while substantially decreasing the typical post-silicon validation time.ITESO, A.C

A Holistic Methodology for System Margining and Jitter Tolerance Optimization in Post-Silicon Validation

The optimization of receiver analog circuitry in modern high-speed input/output (HSIO) links is a very time consuming post-silicon validation process. Current industrial practices are based on exhaustive enumeration methods to improve either the system margins or the jitter tolerance compliance test. In this paper, these two requirements are addressed in a holistic optimization-based approach. We propose an innovative objective function based on these two metrics. Our method employs Kriging to build a surrogate model based on system margining and jitter tolerance measurements. The proposed method is able to deliver optimal system margins and guarantee jitter tolerance compliance while substantially decreasing the typical post-Si validation time

Transmitter and Receiver Equalizers Optimization Methodologies for High-Speed Links in Industrial Computer Platforms Post-Silicon Validation

As microprocessor design scales to nanometric technology, traditional post-silicon validation techniques are inappropriate to get a full system functional coverage. Physical complexity and extreme technology process variations introduce design challenges to guarantee performance over process, voltage, and temperature conditions. In addition, there is an increasingly higher number of mixed-signal circuits within microprocessors. Many of them correspond to high-speed input/output (HSIO) links. Improvements in signaling methods, circuits, and process technology have allowed HSIO data rates to scale beyond 10 Gb/s, where undesired effects can create multiple signal integrity problems. With all of these elements, post-silicon validation of HSIO links is tough and time-consuming. One of the major challenges in electrical validation of HSIO links lies in the physical layer (PHY) tuning process, where equalization techniques are used to cancel these undesired effects. Typical current industrial practices for PHY tuning require massive lab measurements, since they are based on exhaustive enumeration methods. In this work, direct and surrogate-based optimization methods, including space mapping, are proposed based on suitable objective functions to efficiently tune the transmitter and receiver equalizers. The proposed methodologies are evaluated by lab measurements on realistic industrial post-silicon validation platforms, confirming dramatic speed up in PHY tuning and substantial performance improvement

Direct Optimization of a PCI Express Link Equalization in Industrial Post-Silicon Validation

Post-silicon validation is a crucial industrial testing process in modern computer platforms. Post-silicon validation of high-speed input/output (HSIO) links can be critical for making a product release qualification. Peripheral component interconnect express (PCIe) is a high-performance interconnect architecture widely adopted in the computer industry, and one of the most complex HSIO interfaces. PCIe data rates increase on every new generation. To mitigate channel effects due to the increase in transmission speeds, the PCIe specification defines requirements to perform equalization (EQ) at the transmitter (Tx) and at the receiver (Rx). During the EQ process, one combination of Tx/Rx EQ coefficients must be selected to meet the performance requirements of the system. Testing all possible coefficient combinations is prohibitive. Current industrial practice consists of finding a subset of combinations at post-silicon validation using maps of EQ coefficients, which are obtained by measuring the eye height, eye width, and the eye asymmetries of the received signal. Given the large number of electrical parameters and the multiplicity of signal eyes that are produced by on-die probes for observation, finding this subset of coefficients is often a challenge. In order to overcome this problem, a direct optimization method based on a suitable objective function formulation to efficiently tune the Tx and Rx EQ coefficients to successfully comply with the PCIe specification is presented in this report. The proposed optimization approach is based on a low-cost computational procedure combining pattern search and Nelder-Mead methods to efficiently solve an objective function with many local minima, and evaluated by lab measurements on a realistic industrial post-silicon validation platform

Machine Learning Techniques for Electrical Validation Enhancement Processes

Post-Silicon system margin validation consumes a significant amount of time and resources. To overcome this, a reduced validation plan for derivative products has previously been used. However, a certain amount of validation is still needed to avoid escapes, which is prone to subjective bias by the validation engineer comparing a reduced set of derivative validation data against the base product data. Machine Learning techniques allow, to perform automatic decisions and predictions based on already available historical data. In this work, we present an efficient methodology implemented with Machine Learning to make an automatic risk assessment decision and eye margin estimation measurements for derivative products, considering a large set of parameters obtained from the base product. The proposed methodology yields a high performance on the risk assessment decision and the estimation by regression, which translates into a significant reduction in time, effort, and resources