Fusing Temporal Graphs into Transformers for Time-Sensitive Question Answering

Answering time-sensitive questions from long documents requires temporal reasoning over the times in questions and documents. An important open question is whether large language models can perform such reasoning solely using a provided text document, or whether they can benefit from additional temporal information extracted using other systems. We address this research question by applying existing temporal information extraction systems to construct temporal graphs of events, times, and temporal relations in questions and documents. We then investigate different approaches for fusing these graphs into Transformer models. Experimental results show that our proposed approach for fusing temporal graphs into input text substantially enhances the temporal reasoning capabilities of Transformer models with or without fine-tuning. Additionally, our proposed method outperforms various graph convolution-based approaches and establishes a new state-of-the-art performance on SituatedQA and three splits of TimeQA.Comment: EMNLP 2023 Finding

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

Reconfigurable FIR Filter Coefficient Optimization in Post-Silicon Validation to Improve Eye Diagram for Optical Interconnects

Enhanced small form-factor pluggable (SFP+) is a specification for a new generation of optical modular transceivers. The devices are designed for use with small form factor (SFF) connectors, and offer high speed and physical compactness. SFP+ modules require high-quality ASIC/SerDes transmitters (Tx) because IEEE and fibre channel standards place strict requirements on the optical interface, and linear/limiting SFP+ module types have Tx paths that do not correct for timing jitter. This introduces a design challenge to guarantee performance over process, temperature, and voltage (PVT) conditions. Adjusting the Tx equalization across PVT and different interconnect channels can be a time-consuming task in post-silicon validation. In order to overcome this problem, this paper proposes a direct optimization method based on a suitable objective function formulation to efficiently tune the Tx equalizer and optimize the eye diagram to successfully comply with industrial specifications

High-Speed Links Receiver Optimization in Post-Silicon Validation Exploiting Broyden-based Input Space Mapping

One of the major challenges in high-speed input/output (HSIO) links electrical validation is the physical layer (PHY) tuning process. Equalization techniques are employed to cancel any undesired effect. Typical industrial practices require massive lab measurements, making the equalization process very time consuming. In this paper, we exploit the Broyden-based input space mapping (SM) algorithm to efficiently optimize the PHY tuning receiver (Rx) equalizer settings for a SATA Gen 3 channel topology. We use a good-enough surrogate model as the coarse model, and an industrial post-silicon validation physical platform as the fine model. A map between the coarse and the fine model Rx equalizer settings is implicitly built, yielding an accelerated SM-based optimization of the PHY tuning process

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

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 (poster)

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

Post-silicon Receiver Equalization Metamodeling by Artificial Neural Networks

As microprocessor design scales to the 10 nm technology and beyond, traditional pre- and post-silicon validation techniques are unsuitable to get a full system functional coverage. Physical complexity and extreme technology process variations severely limits the effectiveness and reliability of pre-silicon validation techniques. This scenario imposes the need of sophisticated post-silicon validation approaches to consider complex electromagnetic phenomena and large manufacturing fluctuations observed in actual physical platforms. One of the major challenges in electrical validation of high-speed input/output (HSIO) links in modern computer platforms lies in the physical layer (PHY) tuning process, where equalization techniques are used to cancel undesired effects induced by the channels. Current industrial practices for PHY tuning in HSIO links are very time consuming since they require massive lab measurements. An alternative is to use machine learning techniques to model the PHY, and then perform equalization using the resultant surrogate model. In this paper, a metamodeling approach based on neural networks is proposed to efficiently simulate the effects of a receiver equalizer PHY tuning settings. We use several design of experiments techniques to find a neural model capable of approximating the real system behavior without requiring a large amount of actual measurements. We evaluate the models performance by comparing with measured responses on a real server HSIO link