E-QED: Electrical Bug Localization During Post-Silicon Validation Enabled by Quick Error Detection and Formal Methods

During post-silicon validation, manufactured integrated circuits are extensively tested in actual system environments to detect design bugs. Bug localization involves identification of a bug trace (a sequence of inputs that activates and detects the bug) and a hardware design block where the bug is located. Existing bug localization practices during post-silicon validation are mostly manual and ad hoc, and, hence, extremely expensive and time consuming. This is particularly true for subtle electrical bugs caused by unexpected interactions between a design and its electrical state. We present E-QED, a new approach that automatically localizes electrical bugs during post-silicon validation. Our results on the OpenSPARC T2, an open-source 500-million-transistor multicore chip design, demonstrate the effectiveness and practicality of E-QED: starting with a failed post-silicon test, in a few hours (9 hours on average) we can automatically narrow the location of the bug to (the fan-in logic cone of) a handful of candidate flip-flops (18 flip-flops on average for a design with ~ 1 Million flip-flops) and also obtain the corresponding bug trace. The area impact of E-QED is ~2.5%. In contrast, deter-mining this same information might take weeks (or even months) of mostly manual work using traditional approaches

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

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

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

Post-silicon Validation of Radiation Hardened Microprocessor and SRAM arrays

abstract: Digital systems are increasingly pervading in the everyday lives of humans. The security of these systems is a concern due to the sensitive data stored in them. The physically unclonable function (PUF) implemented on hardware provides a way to protect these systems. Static random-access memories (SRAMs) are designed and used as a strong PUF to generate random numbers unique to the manufactured integrated circuit (IC). Digital systems are important to the technological improvements in space exploration. Space exploration requires radiation hardened microprocessors which minimize the functional disruptions in the presence of radiation. The design highly efficient radiation-hardened microprocessor for enabling spacecraft (HERMES) is a radiation-hardened microprocessor with performance comparable to the commercially available designs. These designs are manufactured using a foundry complementary metal-oxide semiconductor (CMOS) 55-nm triple-well process. This thesis presents the post silicon validation results of the HERMES and the PUF mode of SRAM across process corners. Chapter 1 gives an overview of the blocks implemented on the test chip 25. It also talks about the pre-silicon functional verification methodology used for the test chip. Chapter 2 discusses about the post silicon testing setup of test chip 25 and the validation of the setup. Chapter 3 describes the architecture and the test bench of the HERMES along with its testing results. Chapter 4 discusses the test bench and the perl scripts used to test the SRAM along with its testing results. Chapter 5 gives a summary of the post-silicon validation results of the HERMES and the PUF mode of SRAM.Dissertation/ThesisMasters Thesis Electrical Engineering 201

Machine learning techniques and space mapping approaches to enhance signal and power integrity in high-speed links and power delivery networks

Enhancing signal integrity (SI) and reliability in modern computer platforms heavily depends on the post-silicon validation of high-speed input/output (HSIO) links, which implies a physical layer (PHY) tuning process where equalization techniques are employed. On the other hand, the interaction between SI and power delivery networks (PDN) is becoming crucial in the computer industry, imposing the need of computationally expensive models to also ensure power integrity (PI). In this paper, surrogate-based optimization (SBO) methods, including space mapping (SM), are applied to efficiently tune equalizers in HSIO links using lab measurements on industrial post-silicon validation platforms, speeding up the PHY tuning process while enhancing eye diagram margins. Two HSIO interfaces illustrate the proposed SBO/SM techniques: USB3 Gen 1 and SATA Gen 3. Additionally, a methodology based on parameter extraction is described to develop fast PDN lumped models for low-cost SI-PI co-simulation; a dual data rate (DDR) memory sub-system illustrates this methodology. Finally, we describe a surrogate modeling methodology for efficient PDN optimization, comparing several machine learning techniques; a PDN voltage regulator with dual power rail remote sensing illustrates this last methodology.ITESO, A.C

Symbolic QED Pre-silicon Verification for Automotive Microcontroller Cores: Industrial Case Study

We present an industrial case study that demonstrates the practicality and effectiveness of Symbolic Quick Error Detection (Symbolic QED) in detecting logic design flaws (logic bugs) during pre-silicon verification. Our study focuses on several microcontroller core designs (~1,800 flip-flops, ~70,000 logic gates) that have been extensively verified using an industrial verification flow and used for various commercial automotive products. The results of our study are as follows: 1. Symbolic QED detected all logic bugs in the designs that were detected by the industrial verification flow (which includes various flavors of simulation-based verification and formal verification). 2. Symbolic QED detected additional logic bugs that were not recorded as detected by the industrial verification flow. (These additional bugs were also perhaps detected by the industrial verification flow.) 3. Symbolic QED enables significant design productivity improvements: (a) 8X improved (i.e., reduced) verification effort for a new design (8 person-weeks for Symbolic QED vs. 17 person-months using the industrial verification flow). (b) 60X improved verification effort for subsequent designs (2 person-days for Symbolic QED vs. 4-7 person-months using the industrial verification flow). (c) Quick bug detection (runtime of 20 seconds or less), together with short counterexamples (10 or fewer instructions) for quick debug, using Symbolic QED