Xin Li

Conference Mcge 2025 Proceedings of the 3rd International Workshop on Multimedia Content Generation and Evaluation New Methods and Practice Co Located with mm 2025 · October 26, 2025 With the rapid development of social networks,people are increasingly expressing their emotions through tweets on these platforms. This has led to the emergence of Multimodal Aspect-Based Sentiment Classification (MASC), which aims to classify the polarity ... Full text Cite

Decomposition and Foresight: Comparing Human and Simulated Teacher in Preference-Based Reinforcement Learning

Conference Mcge 2025 Proceedings of the 3rd International Workshop on Multimedia Content Generation and Evaluation New Methods and Practice Co Located with mm 2025 · October 26, 2025 Preference-based reinforcement learning (PBRL) algorithms train intelligent agents efficiently by learning reward functions from human preferences, bypassing the need for costly pre-existing reward functions. However, prior PBRL research has predominantly ... Full text Cite

Reviving Mural Art through Generative AI: A Comparative Study of AI-Generated and Hand-Crafted Recreations

Conference Conference on Human Factors in Computing Systems Proceedings · April 26, 2025 Virtual reality (VR) provides an immersive and interactive platform for presenting ancient murals, enhancing users' understanding and appreciation of these invaluable culture treasures. However, traditional hand-crafted methods for recreating murals in VR ... Full text Cite

Intelligent foreign object detection on ballastless track beds via multimodal learning

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2025 The detection of foreign objects on ballastless track beds is critical for ensuring railway operational safety, yet existing manual inspection methods suffer from inefficiency and delayed hazard resolution. This paper proposes a novel multimodal fusion lea ... Full text Cite

Robin: RWKV Accelerator using Block Circulant Matrices based on FPGA

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · January 1, 2025 Recent advancements in linear-attention models, such as RWKV, have opened up new possibilities for efficient sequence processing by reducing the computational overhead of traditional Transformer architectures. Field-programmable gate arrays (FPGAs) offer a ... Full text Cite

Attention Mixture Network for Crowd Counting via Binarization Transfer

Conference Mcge 2024 Proceedings of the 2nd International Workshop on Multimedia Content Generation and Evaluation New Methods and Practice Co Located with mm 2024 · October 28, 2024 Crowd counting endeavors to estimate the numerical count of individuals present within an image depicting a gathering of people. In recent years, there has been notable and gradual advancement in the realm of crowd counting, driven by the integration of at ... Full text Cite

Drive Like a Human: Rethinking Autonomous Driving with Large Language Models

Conference Proceedings 2024 IEEE Winter Conference on Applications of Computer Vision Workshops Wacvw 2024 · January 1, 2024 In this paper, we explore the potential of using a large language model (LLM) to understand the driving environment in a human-like manner and analyze its ability to reason, interpret, and memorize when facing complex scenarios. We argue that traditional o ... Full text Cite

DILU: A KNOWLEDGE-DRIVEN APPROACH TO AUTONOMOUS DRIVING WITH LARGE LANGUAGE MODELS

Conference 12th International Conference on Learning Representations Iclr 2024 · January 1, 2024 Recent advancements in autonomous driving have relied on data-driven approaches, which are widely adopted but face challenges including dataset bias, overfitting, and uninterpretability. Drawing inspiration from the knowledge-driven nature of human driving ... Cite

Causal Discovery for Rechargeable Battery Modeling Considering Group-Level DAG Constraints

Conference IECON Proceedings Industrial Electronics Conference · January 1, 2024 Rechargeable battery has attracted great research popularity in recent years, and numerous data-driven solutions have been proposed for its modeling. While most research works in this domain focus on the statistical correlations among extracted variables, ... Full text Cite

Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving

Conference Advances in Neural Information Processing Systems · January 1, 2024 Autonomous driving has advanced significantly due to sensors, machine learning, and artificial intelligence improvements. However, prevailing methods struggle with intricate scenarios and causal relationships, hindering adaptability and interpretability in ... Cite

Multi-Space Alignments Towards Universal LiDAR Segmentation

Conference Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition · January 1, 2024 A unified and versatile LiDAR segmentation model with strong robustness and generalizability is desirable for safe autonomous driving perception. This work presents M3Net, a one-of-a-kind framework for fulfilling multitask, multi-dataset, multimodality LiD ... Full text Cite

UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase

Conference Proceedings of the IEEE International Conference on Computer Vision · January 1, 2023 Point-, voxel-, and range-views are three representative forms of point clouds. All of them have accurate 3D measurements but lack color and texture information. RGB images are a natural complement to these point cloud views and fully utilizing the compreh ... Full text Cite

Robo3D: Towards Robust and Reliable 3D Perception against Corruptions

Conference Proceedings of the IEEE International Conference on Computer Vision · January 1, 2023 The robustness of 3D perception systems under natural corruptions from environments and sensors is pivotal for safety-critical applications. Existing large-scale 3D perception datasets often contain data that are meticulously cleaned. Such configurations, ... Full text Cite

DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds

Conference Proceedings of the IEEE International Conference on Computer Vision · January 1, 2023 Existing offboard 3D detectors always follow a modular pipeline design to take advantage of unlimited sequential point clouds. We have found that the full potential of off-board 3D detectors is not explored mainly due to two reasons: (1) the onboard multi- ... Full text Cite

LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross- Modal Fusion

Conference Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition · January 1, 2023 LiDAR-camera fusion methods have shown impressive performance in 3D object detection. Recent advanced multi-modal methods mainly perform global fusion, where image features and point cloud features are fused across the whole scene. Such practice lacks fine ... Full text Cite

SCPNet: Semantic Scene Completion on Point Cloud

Conference Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition · January 1, 2023 Training deep models for semantic scene completion (SSC) is challenging due to the sparse and incomplete input, a large quantity of objects of diverse scales as well as the inherent label noise for moving objects. To address the above-mentioned problems, w ... Full text Cite

Semi-Supervised Root-Cause Analysis with Co-Training for Integrated Systems

Conference Proceedings of the IEEE VLSI Test Symposium · January 1, 2022 The increasing complexity of integrated systems has exacerbated the challenges associated with system diagnosis. To tackle these challenges, intelligent root-cause-analysis facilitated by machine learning has been proposed in recent years. However, most of ... Full text Cite

Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detection

Conference Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics · January 1, 2022 Multi-modal 3D object detection has been an active research topic in autonomous driving. Nevertheless, it is non-trivial to explore the cross-modal feature fusion between sparse 3D points and dense 2D pixels. Recent approaches either fuse the image feature ... Full text Cite

Robust Classification with Noisy Labels for Manufacturing Applications: A Hybrid Approach Based on Active Learning and Data Cleaning

Conference IECON Proceedings Industrial Electronics Conference · October 13, 2021 Classification is an important machine learning technique that attracts growing interests in various manufacturing applications. Learning an accurate classifier generally requires a large-scale perfectly-labeled training dataset. However, such "golden"labe ... Full text Cite

Unsupervised root-cause analysis with transfer learning for integrated systems

Conference Proceedings of the IEEE VLSI Test Symposium · April 25, 2021 The increasing complexity of integrated systems has exacerbated the problems associated with root-cause analysis. Leveraging advances artificial intelligence, a large amount of intelligent root-cause-analysis methods have been proposed in recent years. How ... Full text Cite

Unsupervised Root-Cause Analysis for Integrated Systems

Conference Proceedings International Test Conference · November 1, 2020 The increasing complexity and high cost of integrated systems has placed immense pressure on root-cause analysis and diagnosis. In light of artificial intelligent and machine learning, a large amount of intelligent root-cause analysis methods have been pro ... Full text Cite

Margin Guidance Network for Arbitrary-shaped Scene Text Detection

Conference Proceedings International Conference on Tools with Artificial Intelligence Ictai · November 1, 2020 Segmentation-based scene text detection approaches have been adopted to arbitrary-shaped texts and have achieved a great progress. However, false detection always easily exist when the arbitrary-shaped texts are close to each other. In this paper, we propo ... Full text Cite

Exploring Inter-Sensor Correlation for Missing Data Estimation

Conference IECON Proceedings Industrial Electronics Conference · October 18, 2020 Data mining techniques have been widely applied to various fields including industrial, business, and governmental applications. Missing data is a common occurrence in a number of real-world databases, which may substantially affect the accuracy of data pr ... Full text Cite

Fine-grained Adaptive Testing Based on Quality Prediction

Conference ACM Transactions on Design Automation of Electronic Systems · October 1, 2020 The ever-increasing complexity of integrated circuits inevitably leads to high test cost. Adaptive testing provides an effective solution for test-cost reduction; this testing framework selects the important test items for each set of chips. However, adapt ... Full text Cite

A Classification Framework Using Imperfectly Labeled Data for Manufacturing Applications

Conference IEEE International Conference on Emerging Technologies and Factory Automation ETFA · September 1, 2020 In recent years, classification techniques have been broadly adopted for a variety of smart manufacturing applications, including system health maintenance, defect detection and diagnosis, etc. However, most classification methods require a large set of tr ... Full text Cite

Efficient Classification via Partial Co-Training for Virtual Metrology

Conference IEEE International Conference on Emerging Technologies and Factory Automation ETFA · September 1, 2020 Developing accurate and cost-effective classification techniques to facilitate virtual metrology is a critical task for modern manufacturing. In this paper, we consider the scenario in which labeling data is expensive, causing a shortage of labeled data. A ... Full text Cite

Visual-to-Semantic Hashing for Zero Shot Learning

Conference Proceedings of the International Joint Conference on Neural Networks · July 1, 2020 Hashing-based multimedia retrieval are facing the problem of the dramatic increase of data, especially new unseen categories. It is time-consuming, expensive, and sometimes impractical to label new samples and retrain the hashing model. Recently, several z ... Full text Cite

A Real-Time Deep Network for Crowd Counting

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · May 1, 2020 Automatic analysis of highly crowded people has attracted extensive attention from computer vision research. Previous approaches for crowd counting have already achieved promising performance across various benchmarks. However, to deal with the real situat ... Full text Cite

VSB2-Net: Visual-semantic bi-branch network for zero-shot hashing

Conference Proceedings International Conference on Pattern Recognition · January 1, 2020 Zero-shot hashing aims at learning hashing model from seen classes and the obtained model is capable of generalizing to unseen classes for image retrieval. Inspired by zero-shot learning, existing zero-shot hashing methods usually transfer the supervised k ... Full text Cite

Knowledge transfer in board-level functional fault identification using domain adaptation

Conference Proceedings International Test Conference · November 1, 2019 High integration densities and design complexity make board-level functional fault identification extremely difficult. Machine-learning techniques can identify functional faults with high accuracy, but they require a large volume of data to achieve high pr ... Full text Cite

Track Circuit Signal Denoising Method Based on Q-Learning Algorithm

Conference 2019 IEEE Intelligent Transportation Systems Conference ITSC 2019 · October 1, 2019 This paper presents the track circuit signal acquisition procedure and the structure of the receiving antenna. A new track circuit signal noise extraction method by adding a center tap of the receiving antenna is proposed. Furthermore, the Q-learning algor ... Full text Cite

Machine-Learning-Driven Matrix Ordering for Power Grid Analysis

Conference Proceedings of the 2019 Design Automation and Test in Europe Conference and Exhibition Date 2019 · May 14, 2019 A machine-learning-driven approach for matrix ordering is proposed for power grid analysis based on domain decomposition. It utilizes support vector machine or artificial neural network to learn a classifier to automatically choose the optimal ordering alg ... Full text Cite

Black-Box Test-Coverage Analysis and Test-Cost Reduction Based on a Bayesian Network Model

Conference Proceedings of the IEEE VLSI Test Symposium · April 1, 2019 The growing complexity of circuit boards makes manufacturing test increasingly expensive. In order to reduce test cost, a number of test selection methods have been proposed in the literature. However, only few of these methods can be applied to black-box ... Full text Cite

Board-Level Functional Fault Identification using Streaming Data

Conference Proceedings of the IEEE VLSI Test Symposium · April 1, 2019 High integration densities and design complexity of printed-circuit boards make board-level functional fault identification extremely difficult. Machine learning provides an opportunity to identify functional faults with high accuracy and thereby reduce re ... Full text Cite

Model-based and data-driven approaches for building automation and control

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · November 5, 2018 Smart buildings in the future are complex cyber-physical-human systems that involve close interactions among embedded platform (for sensing, computation, communication and control), mechanical components, physical environment, building architecture, and oc ... Full text Cite

Predictive Modeling for Advanced Virtual Metrology: A Tree-Based Approach

Conference IEEE International Conference on Emerging Technologies and Factory Automation ETFA · October 22, 2018 The rapid development of industry 4.0 has promoted the extensive adoption of big data analytics for manufacturing industry. In this domain, virtual metrology is a critical technique that is able to reduce manufacturing cost over a large amount of practical ... Full text Cite

Fine-Grained Adaptive Testing Based on Quality Prediction

Conference Proceedings International Test Conference · July 2, 2018 The ever-increasing complexity of integrated circuits inevitably leads to high test cost. Adaptive testing provides an effective solution for test-cost reduction; this testing framework selects the important test items for each set of chips. However, adapt ... Full text Cite

MiniTracker: A Lightweight CNN-based System for Visual Object Tracking on Embedded Device

Conference International Conference on Digital Signal Processing DSP · July 2, 2018 Visual object tracking (VOT) is a computer vision application and has a wide range of use. However, related state of the art algorithms using deep learning methods, are computationally intensive and storage explosive. Whats more, despite many deep learning ... Full text Cite

Single-Channel Real-Time Drowsiness Detection Based on Electroencephalography.

Conference Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · July 2018 The need of a reliable drowsiness detection system is arising today, as drowsiness is considered as a major cause for accidents as much as alcohol. In this paper, we propose a real-time drowsiness detection algorithm based on a single-channel electroenceph ... Full text Cite

An efficient audio based performance evaluation system for computer assisted piano learning

Conference Icnc Fskd 2017 13th International Conference on Natural Computation Fuzzy Systems and Knowledge Discovery · June 21, 2018 In this paper, we propose an audio based piano performance evaluation system for piano learning, aiming at giving objective feedbacks to the piano beginners so that their self-practicing could be more efficient. We target to build a system which could eval ... Full text Cite

Intelligent corner synthesis via cycle-consistent generative adversarial networks for efficient validation of autonomous driving systems

Conference Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC · February 20, 2018 Today's automotive vehicles are often equipped with powerful data processing systems for driver assistance and/or autonomous driving. To meet the rigorous safety standard, one critical task is to ensure extremely small failure rate over all possible operat ... Full text Cite

Message from the general chairs

Conference Proceedings 2017 IEEE International Symposium on Nanoelectronic and Information Systems Inis 2017 · February 15, 2018 Full text Cite

Impact of circuit-level non-idealities on vision-based autonomous driving systems

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · December 13, 2017 We describe a novel methodology to validate vision-based autonomous driving systems over different circuit corners with consideration of temperature variation and circuit aging. The proposed work is motivated by the fact that low-level circuit implementati ... Full text Cite

Efficient programming of reconfigurable radio frequency (RF) systems

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · December 13, 2017 Reconfigurable radio frequency (RF) system has recently emerged as a promising solution to cope with multiple communication standards and high spectrum density. In this paper, we propose a novel optimization framework to efficiently program a reconfigurabl ... Full text Cite

A configurable nonlinear operation unit for neural network accelerator

Conference Proceedings of International Conference on ASIC · July 1, 2017 With the development of machine learning, neural network accelerators are widely used to speed up the calculation. Many of the accelerators are designed to be configurable so they can be widely used in different situations. Nonlinear operation is essential ... Full text Cite

A high utilization FPGA-based accelerator for variable-scale convolutional neural network

Conference Proceedings of International Conference on ASIC · July 1, 2017 Convolutional Neural Network (CNN) plays an essential role in computer vision applications for high classification accuracy and robust generalization capability. In recent years, various GPU-based or application-specific hardware approaches have been propo ... Full text Cite

Partial Co-training for virtual metrology

Conference IEEE International Conference on Emerging Technologies and Factory Automation ETFA · June 28, 2017 Virtual metrology is an important tool for industrial automation. To accurately build regression models for virtual metrology, we consider semi-supervised learning where labeled data are expensive to collect, but unlabeled data are abundant. In such a scen ... Full text Cite

Correlated Rare Failure Analysis via Asymptotic Probability Evaluation

Conference Proceedings Design Automation Conference · June 18, 2017 In this paper, a novel Asymptotic Probability Estimation (APE) method is proposed to estimate the probability of correlated rare failure events for complex integrated systems containing a large number of replicated cells. The key idea is to approximate the ... Full text Cite

Efficient Hierarchical Performance Modeling for Integrated Circuits via Bayesian Co-Learning

Conference Proceedings Design Automation Conference · June 18, 2017 With the continuous drive towards integrated circuits scaling, efficient performance modeling is becoming more crucial yet, more challenging. In this paper, we propose a novel method of hierarchical performance modeling based on Bayesian co-learning. We ex ... Full text Cite

Compressive spectral anomaly detection

Conference 2017 IEEE International Conference on Computational Photography Iccp 2017 Proceedings · June 16, 2017 We propose a novel compressive imager for detecting anomalous spectral profiles in a scene. We model the background spectrum as a low-dimensional subspace while assuming the anomalies to form a spatially-sparse set of spectral profiles different from the b ... Full text Cite

An audio based piano performance evaluation method using deep neural network based acoustic modeling

Conference Proceedings of the Annual Conference of the International Speech Communication Association Interspeech · January 1, 2017 In this paper, we propose an annotated piano performance evaluation dataset with 185 audio pieces and a method to evaluate the performance of piano beginners based on their audio recordings. The proposed framework includes three parts: piano key posterior ... Full text Cite

Aggregated load and generation equivalent circuit models with semi-empirical data fitting

Conference 2016 IEEE Green Energy and Systems Conference Igsec 2016 · December 16, 2016 In this paper we propose a semi-empirical modeling framework for aggregated electrical load and generation using an equivalent circuit formulation. The proposed models are based on complex rectangular voltage and current state variables that provide a gene ... Full text Cite

Unified power system analyses and models using equivalent circuit formulation

Conference 2016 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference Isgt 2016 · December 9, 2016 In this paper we propose and demonstrate the potential for unifying models and algorithms for the steady state and transient simulation of single-phase and three-phase power systems. At present, disparate algorithms and models are used for the different an ... Full text Cite

Efficient statistical analysis for correlated rare failure events via asymptotic probability approximation

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · November 7, 2016 In this paper, a novel Asymptotic Probability Approximation (APA) method is proposed to estimate the overall rare probability of correlated failure events for complex circuits containing a large number of replicated cells (e.g., SRAM bit-cells). The key id ... Full text Cite

Efficient statistical validation of machine learning systems for autonomous driving

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · November 7, 2016 Today's automotive industry is making a bold move to equip vehicles with intelligent driver assistance features. A modern automobile is now equipped with a powerful computing platform to run multiple machine learning algorithms for environment perception ( ... Full text Cite

Overview of cyber-physical temperature estimation in smart buildings: From modeling to measurements

Conference Proceedings IEEE INFOCOM · September 6, 2016 Smart buildings are playing a more important role in everyday lives of people. One important goal of creating smart buildings is to offer highly comfortable services to the occupants at the lowest cost. In-building temperature modeling and measurement is a ... Full text Cite

Message from the general chairs

Conference Proceedings of IEEE Computer Society Annual Symposium on VLSI Isvlsi · September 2, 2016 Full text Cite

Cross-scale predictive dictionaries for image and video restoration

Conference Proceedings International Conference on Image Processing Icip · August 3, 2016 We propose a novel signal model, based on sparse representations, that captures cross-scale features for visual signals. We show that cross-scale predictive model enables faster solutions to sparse approximation problems. This is achieved by first solving ... Full text Cite

Identifying systematic spatial failure patterns through wafer clustering

Conference Proceedings IEEE International Symposium on Circuits and Systems · July 29, 2016 In this paper, we propose a novel methodology for detecting systematic spatial failure patterns at wafer level for yield learning. Our proposed methodology takes the testing results (i.e., pass or fail) of a number of dies over different wafers, cluster al ... Full text Cite

Virtual temperature measurement for smart buildings via Bayesian model fusion

Conference Proceedings IEEE International Symposium on Circuits and Systems · July 29, 2016 One important goal of creating smart buildings is to offer highly comfortable services to the occupants at low cost. Real-time temperature measurement and monitoring is a critical task to facilitate high-quality service with low energy consumption and, hen ... Full text Cite

An equivalent circuit formulation for three-phase power flow analysis of distribution systems

Conference Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference · July 22, 2016 In this paper, we describe a power flow formulation for 3-phase distribution systems that is based on an equivalent circuit model. It is shown that this physical model based solution is able to accommodate a wide range of complex and unbalanced loads witho ... Full text Cite

Improving robustness and modeling generality for power flow analysis

Conference Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference · July 22, 2016 In this paper we present an equivalent circuit model for power system networks that facilitates robust and efficient AC power flow simulation and enables the incorporation of more generalized bus and line models. The circuit equations are formulated in ter ... Full text Cite

Steady-state analysis of power system harmonics using equivalent split-circuit models

Conference IEEE Pes Innovative Smart Grid Technologies Conference Europe · July 2, 2016 In this paper we introduce a novel algorithm for harmonic steady-state analysis of power systems that is based on the equivalent split-circuit models recently introduced for power flow analysis. By using an equivalent circuit with current and voltage as th ... Full text Cite

Diagnostic resolution improvement through learning-guided physical failure analysis

Conference Proceedings International Test Conference · July 2, 2016 An accurate and high-resolution diagnosis enables physical failure analysis (PFA) to identify and understand the root-cause of integrated-circuit failure. Despite many existing techniques for improving diagnosis, resolution is still far from ideal, which h ... Full text Cite

Correlated Bayesian Model Fusion: Efficient performance modeling of large-scale tunable analog/RF integrated circuits

Conference Proceedings Design Automation Conference · June 5, 2016 Tunable circuit has emerged as a promising methodology to address the grand challenge posed by process variations. Efficient high-dimensional performance modeling of tunable analog/RF circuits is an important yet challenging task. In this paper, we propose ... Full text Cite

Efficient analog circuit optimization using sparse regression and error margining

Conference Proceedings International Symposium on Quality Electronic Design Isqed · May 25, 2016 In this paper, we propose a novel analog circuit optimization methodology for achieving high parametric yield. We solve the statistical worst-case optimization problem by a sequence of linear programings where performance metrics are fitted using sparse re ... Full text Cite

Efficient spatial variation modeling via robust dictionary learning

Conference Proceedings of the 2016 Design Automation and Test in Europe Conference and Exhibition Date 2016 · April 25, 2016 In this paper, we propose a novel spatial variation modeling method based on robust dictionary learning for nanoscale integrated circuits. This method takes advantage of the historical data to efficiently improve the accuracy of wafer-level spatial variati ... Full text Cite

Parasitic-aware common-centroid FinFET placement and routing for current-ratio matching

Conference ACM Transactions on Design Automation of Electronic Systems · April 1, 2016 The FinFET technology is regarded as a better alternative for modern high-performance and low-power integrated-circuit design due to more effective channel control and lower power consumption. However, the gate-misalignment problem resulting from process v ... Full text Cite

Energy efficient learning and classification for distributed sensing

Conference 2016 8th International Conference on Communication Systems and Networks Comsnets 2016 · March 23, 2016 In order to reduce total energy communicated by distributed sensors, we address the problem where the recipient wants to perform supervised learning and classification on the data received from the sensors. Restricting our attention to a noiseless communic ... Full text Cite

Re-thinking polynomial optimization: Efficient programming of reconfigurable radio frequency (RF) systems by convexification

Conference Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC · March 7, 2016 Reconfigurable radio frequency (RF) system has emerged as a promising avenue to achieve high communication performance while adapting to versatile commercial wireless environment. In this paper, we propose a novel technique to optimally program a reconfigu ... Full text Cite

Thermal modeling for energy-efficient smart building with advanced overfitting mitigation technique

Conference Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC · March 7, 2016 Building energy accounts large amount of the total energy consumption, and smart building energy control leads to high energy efficiency and significant energy savings. A compact and accurate building thermal model is important for designing the efficient ... Full text Cite

Statistical rare event analysis using smart sampling and parameter guidance

Conference International System on Chip Conference · February 12, 2016 In this paper, we propose a new efficient statistical method for failure probability estimation of analog circuits with rate failure events, which is a time-consuming process using the existing Monte Carlo method. On top of this, the new method can also pr ... Full text Cite

Co-Learning Bayesian Model Fusion: Efficient performance modeling of analog and mixed-signal circuits using side information

Conference 2015 IEEE ACM International Conference on Computer Aided Design Iccad 2015 · January 5, 2016 Efficient performance modeling of today's analog and mixed-signal (AMS) circuits is an important yet challenging task. In this paper, we propose a novel performance modeling algorithm that is referred to as Co-Learning Bayesian Model Fusion (CL-BMF). The k ... Full text Cite

From robust chip to smart building: CAD algorithms and methodologies for uncertainty analysis of building performance

Conference 2015 IEEE ACM International Conference on Computer Aided Design Iccad 2015 · January 5, 2016 Buildings consume about 40% of the total energy use in the U.S. and, hence, accurately modeling, analyzing and optimizing building energy is considered as an extremely important task today. Towards this goal, uncertainty/sensitivity analysis has been propo ... Full text Cite

Learning based compact thermal modeling for energy-efficient smart building management

Conference 2015 IEEE ACM International Conference on Computer Aided Design Iccad 2015 · January 5, 2016 In this article, we propose a new behavioral thermal modeling method for fast building performance analysis, which is critical for energy-efficient smart building control and management. The new approach is based on two recurrent neutral network architectu ... Full text Cite

Statistical learning in chip (SLIC)

Conference 2015 IEEE ACM International Conference on Computer Aided Design Iccad 2015 · January 5, 2016 Despite best efforts, integrated systems are born (manufactured) with a unique 'personality' that stems from our inability to precisely fabricate their underlying circuits, and create software a priori for controlling the resulting uncertainty. It is possi ... Full text Cite

Energy-efficient wireless temperature sensoring for smart building applications

Conference 2016 13th IEEE International Conference on Solid State and Integrated Circuit Technology Icsict 2016 Proceedings · January 1, 2016 Building energy accounts for large amount of the total energy consumption, and smart building energy control leads to high energy efficiency and significant energy savings. For energy-efficient smart building applications, accurate and robust measurement o ... Full text Cite

Efficient Performance Modeling via Dual-Prior Bayesian Model Fusion for Analog and Mixed-Signal Circuits

Conference Proceedings Design Automation Conference · January 1, 2016 In this paper, we propose a novel Dual-Prior Bayesian Model Fusion (DP-BMF) algorithm for performance modeling. Different from the previous BMF methods which use only one source of prior knowledge, DP-BMF takes advantage of multiple sources of prior knowle ... Full text Cite

Efficient Performance Modeling of Analog Integrated Circuits via Kernel Density Based Sparse Regression

Conference Proceedings Design Automation Conference · January 1, 2016 With the aggressive scaling of integrated circuit technology, analog performance modeling is facing enormous challenges due to high-dimensional variation space and expensive transistor-level simulation. In this paper, we propose a kernel density based spar ... Full text Cite

A low-cost and energy-efficient EEG processor for continuous seizure detection using wavelet transform and AdaBoost

Conference Proceedings 2016 IEEE Biomedical Circuits and Systems Conference Biocas 2016 · January 1, 2016 A 16-channel, low-complexity and energy-efficient electroencephalography (EEG) processor for patient-specific seizure detection is presented. The feature extraction algorithm extracts line length features from approximation coefficients from a low-overhead ... Full text Cite

A 18mW, 3.3dB NF, 60GHz LNA in 32nm SOI CMOS technology with autonomic NF calibration

Conference Digest of Papers IEEE Radio Frequency Integrated Circuits Symposium · November 25, 2015 A self-healing mmWave SoC integrating an 8052 microcontroller with 12kB of memory, an ADC, a temperature sensor, and a 3-stage cascode 60GHz LNA, implemented in a 32nm SOI CMOS technology exhibits a peak gain of 21dB, an average 3.3dB NF from 53 to 62GHz a ... Full text Cite

Fast statistical analysis of rare circuit failure events via Bayesian scaled-sigma sampling for high-dimensional variation space

Conference Proceedings of the Custom Integrated Circuits Conference · November 25, 2015 Accurately estimating the rare failure events of nanoscale ICs in a high-dimensional variation space is extremely challenging. In this paper, we propose a novel Bayesian scaled-sigma sampling (BSSS) technique to address this technical challenge. BSSS can b ... Full text Cite

A robust and efficient power series method for tracing PV curves

Conference 2015 North American Power Symposium Naps 2015 · November 20, 2015 Estimating the voltage collapse point of a power grid is an important problem in power flow analysis. In this paper, we propose a novel power series method (PSM) for tracing the power-voltage (PV) curve and estimating the collapse point. By expanding the p ... Full text Cite

An equivalent circuit formulation of the power flow problem with current and voltage state variables

Conference 2015 IEEE Eindhoven Powertech Powertech 2015 · August 31, 2015 Steady state analysis of power grids is typically performed using power flow analysis, where nonlinear balance equations of real and reactive power are solved to calculate the voltage magnitude, phase, and power at every bus. Transient analysis of the same ... Full text Cite

Vortex: Variation-aware training for memristor X-bar

Conference Proceedings Design Automation Conference · July 24, 2015 Recent advances in development of memristor devices and cross-bar integration allow us to implement a low-power on-chIP neuromorphic computing system (NCS) with small footprint. Training methods have been proposed to program the memristors in a crossbar by ... Full text Cite

An EDA framework for large scale hybrid neuromorphic computing systems

Conference Proceedings Design Automation Conference · July 24, 2015 In implementations of neuromorphic computing systems (NCS), memristor and its crossbar topology have been widely used to realize fully connected neural networks. However, many neural networks utilized in real applications often have a sparse connectivity, ... Full text Cite

MTunes: Efficient post-silicon tuning of mixed-signal/RF integrated circuits based on Markov decision process

Conference Proceedings Design Automation Conference · July 24, 2015 Uncertainty prevails in IC manufacturing and circuit operation. In particular, process variability has a huge impact on circuit performance, especially for mixed-signal/RF circuits, leading to unacceptable yields. Additionally, environmental uncertainties, ... Full text Cite

Efficient multivariate moment estimation via Bayesian model fusion for analog and mixed-signal circuits

Conference Proceedings Design Automation Conference · June 7, 2015 A critical-yet-challenging problem of analog/mixed-signal circuit validation in either pre-silicon or post-silicon stage is to estimate the parametric yield of the performances. In this paper, we propose a novel Bayesian model fusion method for efficient m ... Full text Cite

Feasibility study of a dual-gate photosensitive thin-film transistor for fingerprint sensor integrated active-matrix display

Conference Digest of Technical Papers SID International Symposium · June 1, 2015 By placing a transparent conductive ITO layer atop a display driver thin-film transistor (TFT), a dual-gate photosensitive TFT is formed to integrate a fingerprint sensing function in a display pixel An analytical model is proposed to elaborate its working ... Full text Cite

EDA challenges for memristor-crossbar based neuromorphic computing

Conference Proceedings of the ACM Great Lakes Symposium on VLSI Glsvlsi · May 20, 2015 The increasing gap between the high data processing capability of modern computing systems and the limited memory bandwidth motivated the recent significant research on neuromorphic computing systems (NCS), which are inspired from the working mechanism of ... Full text Cite

A fast spatial variation modeling algorithm for efficient test cost reduction of analog/RF circuits

Conference Proceedings Design Automation and Test in Europe Date · April 22, 2015 In this paper, we adopt a novel numerical algorithm, referred to as dual augmented Lagrangian method (DALM), for efficient test cost reduction based on spatial variation modeling. The key idea of DALM is to derive the dual formulation of the L1- ... Full text Cite

Efficient bit error rate estimation for high-speed link by Bayesian model fusion

Conference Proceedings Design Automation and Test in Europe Date · April 22, 2015 High-speed I/O link is an important component in computer systems, and estimating its bit error rate (BER) is a critical task to guarantee its performance. In this paper, we propose an efficient method to estimate BER by Bayesian Model Fusion. Its key idea ... Full text Cite

Fast deployment of alternate analog test using Bayesian model fusion

Conference Proceedings Design Automation and Test in Europe Date · April 22, 2015 In this paper, we address the problem of limited training sets for learning the regression functions in alternate analog test. Typically, a large volume of real data needs to be collected from different wafers and lots over a long period of time to be able ... Full text Cite

Common-centroid FinFET placement considering the impact of gate misalignment

Conference Proceedings of the International Symposium on Physical Design · March 29, 2015 The FinFET technology has been regarded as a better alternative among different device technologies at 22nm node and beyond due to more effective channel control and lower power consumption. However, the gate misalignment problem resulting from process var ... Full text Cite

SIPredict: Efficient post-layout waveform prediction via System Identification

Conference 20th Asia and South Pacific Design Automation Conference ASP DAC 2015 · March 11, 2015 In this paper, we propose a post-layout waveform prediction method by System Identification (SI) based on the fact that the waveforms of pre-layout and post-layout are always correlated. Mathematical models are built to describe the relationships between t ... Full text Cite

Fast statistical analysis of rare failure events for memory circuits in high-dimensional variation space

Conference 20th Asia and South Pacific Design Automation Conference ASP DAC 2015 · March 11, 2015 Accurately estimating the rare failure rates for nanoscale memory circuits is a challenging task, especially when the variation space is high-dimensional. In this paper, we summarize two novel techniques to address this technical challenge. First, we descr ... Full text Cite

Accurate passivity-enforced macromodeling for RF circuits via iterative zero/pole update based on measurement data

Conference 20th Asia and South Pacific Design Automation Conference ASP DAC 2015 · March 11, 2015 Passive macromodeling for RF circuit blocks is a critical task to facilitate efficient system-level simulation for large-scale RF systems (e.g., wireless transceivers). In this paper we propose a novel algorithm to find the optimal macromodel that minimize ... Full text Cite

Bayesian model fusion: Enabling test cost reduction of analog/RF circuits via wafer-level spatial variation modeling

Conference Proceedings - International Test Conference · February 6, 2015 In this paper, a novel Bayesian model fusion (BMF) method is proposed for test cost reduction based on wafer-level spatial variation modeling. BMF relies on the assumption that a large number of wafers of the same circuit design (e.g., all wafers from the ... Full text Cite

SLIC: Statistical learning in chip

Conference Proceedings of the 14th International Symposium on Integrated Circuits Isic 2014 · February 2, 2015 Despite best efforts, integrated systems are 'born' (manufactured) with a unique 'personality' that stems from our inability to precisely fabricate their underlying circuits, and create software a priori for controlling the resulting uncertainty. It is pos ... Full text Cite

Ultra-low-power biomedical circuit design and optimization: Catching the don't cares

Conference Proceedings of the 14th International Symposium on Integrated Circuits Isic 2014 · February 2, 2015 To reduce healthcare cost while simultaneously delivering high-quality health services, developing new portable and/or implantable biomedical devices is of great importance for both health monitoring and clinical treatment. In this paper, we describe a rad ... Full text Cite

Reduction and IR-drop compensations techniques for reliable neuromorphic computing systems

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · January 5, 2015 Neuromorphic computing system (NCS) is a promising architecture to combat the well-known memory bottleneck in Von Neumann architecture. The recent breakthrough on memristor devices made an important step toward realizing a low-power, small-footprint NCS on ... Full text Cite

MPME-DP: Multi-population moment estimation via dirichlet process for efficient validation of analog/mixed-signal circuits

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · January 5, 2015 Moment estimation is one of the most important tasks to appropriately characterize the performance variability of today's nanoscale integrated circuits. In this paper, we propose an efficient algorithm of multi-population moment estimation via Dirichlet Pr ... Full text Cite

Fast statistical analysis of rare circuit failure events via subset simulation in high-dimensional variation space

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · January 5, 2015 In this paper, we propose a novel subset simulation (SUS) technique to efficiently estimate the rare failure rate for nanoscale circuit blocks (e.g., SRAM, DFF, etc.) in high-dimensional variation space. The key idea of SUS is to express the rare failure p ... Full text Cite

Phase noise impairment and environment-adaptable fast (EAF) optimization for programming of reconfigurable radio frequency (RF) receivers

Conference Proceedings IEEE Global Communications Conference Globecom · January 1, 2015 In order to support a multi-standard platform, a reconfigurable RF front-end needs an optimal configuration that adapts to a dynamic communication condition. To find an optimal configuration efficiently, we previously proposed the Environment-Adaptable Fas ... Full text Cite

A statistical methodology for noise sensor placement and full-chIP voltage map generation

Conference Proceedings - Design Automation Conference · January 1, 2015 © 2015 ACM. Noise margin violation, also known as voltage emergency induced by continuously reducing noise margin and increasing magnitude of current swings, is becoming a severe threat to the correct execution of applications in processors. Noise sensors ... Full text Cite

Optimal storage sizing using two-stage stochastic optimization for intra-hourly dispatch

Conference 2014 North American Power Symposium Naps 2014 · November 21, 2014 With the increasing penetration of renewable energy sources into the electric power grid, a heightened amount of attention is being given to the topic of energy storage, a popular solution to account for the variability of these sources. Energy storage sys ... Full text Cite

Environment-adaptable efficient optimization for programming of reconfigurable radio frequency (RF) receivers

Conference Proceedings IEEE Military Communications Conference MILCOM · November 13, 2014 Software defined radio has been developed for supporting multi-standard radio receivers, but remains vulnerable to interference. In order to overcome this interference challenge, this paper proposes replacing the fixed wide-band Radio Frequency (RF) front- ... Full text Cite

Toward efficient programming of reconfigurable radio frequency (RF) receivers

Conference Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC · March 27, 2014 Reconfigurable radio frequency (RF) system is an emerging component to mitigate the growing engineering cost for wireless chip design. In this paper, we propose a new methodology for efficient programming of reconfigurable RF receiver. The proposed method ... Full text Cite

Joint invariant estimation of RF impairments for reconfigurable Radio Frequency(RF) front-end

Conference 2014 IEEE Globecom Workshops GC Wkshps 2014 · March 18, 2014 To support a multi-standard platform using Software Defined Radio (SDR), reconfigurable Radio Frequency (RF) front-ends have recently been proposed as a more reliable front-end than the currently used fixed wide-band RF front-ends. With these reconfigurabl ... Full text Cite

Using relative-relevance of data pieces for efficient communication, with an application to Neural data acquisition

Conference 2014 52nd Annual Allerton Conference on Communication Control and Computing Allerton 2014 · January 30, 2014 In this paper, we consider the problem of communicating data from distributed sensors for the goal of inference. Two inference problems of linear regression and binary linear classification are investigated. Assuming perfect training of the classifier, an ... Full text Cite

DALM-SVD: Accelerated sparse coding through singular value decomposition of the dictionary

Conference 2014 IEEE International Conference on Image Processing Icip 2014 · January 28, 2014 Sparse coding techniques have seen an increasing range of applications in recent years, especially in the area of image processing. In particular, sparse coding using ℓ1-regularization has been efficiently solved with the Augmented Lagrangian (A ... Full text Cite

Low-power hardware implementation of movement decoding for brain computer interface with reduced-resolution discrete cosine transform.

Conference Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · January 2014 This paper describes a low-power hardware implementation for movement decoding of brain computer interface. Our proposed hardware design is facilitated by two novel ideas: (i) an efficient feature extraction method based on reduced-resolution discrete cosi ... Full text Cite

Verification based ECG biometrics with cardiac irregular conditions using heartbeat level and segment level information fusion

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · January 1, 2014 We propose an ECG based robust human verification system for both healthy and cardiac irregular conditions using the heartbeat level and segment level information fusion. At the heartbeat level, we first propose a novel beat normalization and outlier remov ... Full text Cite

Computer-aided design of machine learning algorithm: Training fixed-point classifier for on-chip low-power implementation

Conference Proceedings Design Automation Conference · January 1, 2014 In this paper, we propose a novel linear discriminant analysis algorithm, referred to as LDA-FP, to train on-chip classifiers that can be implemented with low-power fixed-point arithmetic with extremely small word length. LDA-FP incorporates the nonidealit ... Full text Cite

BMF-BD: Bayesian model fusion on bernoulli distribution for efficient yield estimation of integrated circuits

Conference Proceedings Design Automation Conference · January 1, 2014 Accurate yield estimation is one of the important yet challenging tasks for both pre-silicon verification and post-silicon validation. In this paper, we propose a novel method of Bayesian model fusion on Bernoulli distribution (BMF-BD) for efficient yield ... Full text Cite

Bayesian Model Fusion: A statistical framework for efficient pre-silicon validation and post-silicon tuning of complex analog and mixed-signal circuits

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · December 1, 2013 In this paper, we describe a novel statistical framework, referred to as Bayesian Model Fusion (BMF), that allows us to minimize the simulation and/or measurement cost for both pre-silicon validation and post-silicon tuning of analog and mixed-signal (AMS) ... Full text Cite

DREAMS: DFM rule evaluation using manufactured silicon

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · December 1, 2013 DREAMS (DFM Rule EvAluation using Manufactured Silicon) is a comprehensive methodology for evaluating the yield-preserving capabilities of a set of DFM (design for manufacturability) rules using the results of logic diagnosis performed on failed ICs. DREAM ... Full text Cite

Fast statistical analysis of rare circuit failure events via scaled-sigma sampling for high-dimensional variation space

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · December 1, 2013 Accurately estimating the rare failure rates for nanoscale circuit blocks (e.g., SRAM, DFF, etc.) is a challenging task, especially when the variation space is high-dimensional. In this paper, we propose a novel scaled-sigma sampling (SSS) method to addres ... Full text Cite

Jacobian singularities in optimal power flow problems caused by intertemporal constraints

Conference 45th North American Power Symposium Naps 2013 · December 1, 2013 In multi-timestep Optimal Power Flow (OPF) formulations, constraints that are time-dependent such as generator ramp limits and specifically energy storage constraints may cause the Jacobian matrix to become singular as the problem iterates towards the opti ... Full text Cite

Test data analytics - Exploring spatial and test-item correlations in production test data

Conference Proceedings International Test Conference · December 1, 2013 The discovery of patterns and correlations hidden in the test data could help reduce test time and cost. In this paper, we propose a methodology and supporting statistical regression tools that can exploit and utilize both spatial and inter-test-item corre ... Full text Cite

PADRE: Physically-aware diagnostic resolution enhancement

Conference Proceedings International Test Conference · December 1, 2013 Diagnosis is the first step of IC failure analysis. The conventional objective of identifying the failure locations has been augmented with various physically-aware techniques that are intended to improve both diagnostic resolution and accuracy. Despite th ... Full text Cite

Strip-and-zone micro-channel liquid cooling of integrated circuits chips with non-uniform power distributions

Conference ASME 2013 Heat Transfer Summer Conf Collocated with the ASME 2013 7th Int Conf on Energy Sustainability and the ASME 2013 11th Int Conf on Fuel Cell Science Engineering and Technology Ht 2013 · December 1, 2013 For a high-power integrated circuit (IC), it is desirable to cool with the liquid micro-channels. However, the non-uniform power distribution of the IC is a great challenge. In this paper, the strip-and-zone strategy is presented. First, the optimal channe ... Full text Cite

Structure-aware high-dimensional performance modeling for analog and mixed-signal circuits

Conference Proceedings of the Custom Integrated Circuits Conference · November 7, 2013 Efficient high-dimensional performance modeling of nanoscale analog and mixed signal (AMS) circuits is extremely challenging. In this paper, we propose a novel structure-aware modeling (SAM) technique. The key idea of SAM is to accurately solve the model c ... Full text Cite

Indirect performance sensing for on-chip analog self-healing via Bayesian model fusion

Conference Proceedings of the Custom Integrated Circuits Conference · November 7, 2013 On-chip analog self-healing requires low-cost sensors to accurately measure various performance metrics. In this paper we propose a novel approach of indirect performance sensing based upon Bayesian model fusion (BMF) to facilitate inexpensive-yet-accurate ... Full text Cite

Referee consensus: A platform technology for nonlinear optimization

Conference ACM International Conference Proceeding Series · August 26, 2013 Electrical current flow within populations of neurons is a fundamental constituent of brain function. The resulting fluctuating magnetic fields may be sampled noninvasively with an array of magnetic field detectors positioned outside the head. This is magn ... Full text Cite

Automatic clustering of wafer spatial signatures

Conference Proceedings Design Automation Conference · July 12, 2013 In this paper, we propose a methodology based on unsupervised learning for automatic clustering of wafer spatial signatures to aid yield improvement. Our proposed methodology is based on three steps. First, we apply sparse regression to automatically captu ... Full text Cite

Efficient moment estimation with extremely small sample size via bayesian inference for analog/mixed-signal validation

Conference Proceedings Design Automation Conference · July 12, 2013 A critical problem in pre-Silicon and post-Silicon validation of analog/mixed-signal circuits is to estimate the distribu- tion of circuit performances, from which the probability of failure and parametric yield can be estimated at all circuit configuratio ... Full text Cite

Bayesian model fusion: Large-scale performance modeling of analog and mixed-signal circuits by reusing early-stage data

Conference Proceedings Design Automation Conference · July 12, 2013 Efficient high-dimensional performance modeling of today's complex analog and mixed-signal (AMS) circuits with large-scale process variations is an important yet challenging task. In this paper, we propose a novel performance modeling algorithm that is ref ... Full text Cite

Optimal integration of intermittent energy sources using distributed multi-step optimization

Conference IEEE Power and Energy Society General Meeting · December 11, 2012 The integration of renewable energy sources such as wind and solar into the electric power grid is a coveted yet challenging goal. The difficulties arise from the intermittency of the sources, the required increase in transmission capacity, and the lack of ... Full text Cite

Inclusion of inter-temporal constraints into a distributed Newton-Raphson method

Conference 2012 North American Power Symposium Naps 2012 · December 10, 2012 Newton-Raphson based methods are widely used for solving Optimal Power Flow (OPF) problems. Convergence can be sensitive to the starting point of the algorithm, the step size, and the condition number of the Jacobian. The inclusion of inter-temporal constr ... Full text Cite

Modeling local variation of low-frequency noise in MOSFETs via sum of lognormal random variables

Conference Proceedings of the Custom Integrated Circuits Conference · November 26, 2012 In this paper, we investigate the geometry dependence for the local variation of low-frequency noise in MOSFETs via the sum of lognormal random variables. A compact model has been developed and applied to the measured data with excellent match, and therefo ... Full text Cite

Large-scale statistical performance modeling of analog and mixed-signal circuits

Conference Proceedings of the Custom Integrated Circuits Conference · November 26, 2012 The aggressive scaling of IC technology results in large-scale performance variations that cannot be efficiently captured by traditional modeling techniques. This paper presents the recent development of statistical performance modeling and its important a ... Full text Cite

Spatial variation decomposition via sparse regression

Conference ICICDT 2012 IEEE International Conference on Integrated Circuit Design and Technology · August 13, 2012 In this paper, we briefly discuss the recent development of a novel sparse regression technique that aims to accurately decompose process variation into two different components: (1) spatially correlated variation, and (2) uncorrelated random variation. Su ... Full text Cite

An information-theoretic framework for optimal temperature sensor allocation and full-chip thermal monitoring

Conference Proceedings Design Automation Conference · July 11, 2012 Full-chip thermal monitoring is an important and challenging issue in today's microprocessor design. In this paper, we propose a new information-theoretic framework to quantitatively model the uncertainty of on-chip temperature variation by differential en ... Full text Cite

Statistical design and optimization for adaptive post-silicon tuning of MEMS filters

Conference Proceedings Design Automation Conference · July 11, 2012 Large-scale process variations can significantly limit the practical utility of microelectro-mechanical systems (MEMS) for RF (radio frequency) applications. In this paper we describe a novel technique of adaptive post-silicon tuning to reliably design MEM ... Full text Cite

A learning-based autoregressive model for fast transient thermal analysis of chip-multiprocessors

Conference Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC · April 26, 2012 Thermal issues have become critical roadblocks for the development of advanced chip-multiprocessors (CMPs). In this paper, we introduce a new angle to view transient thermal analysis - based on predicting thermal profile, instead of calculating it. We deve ... Full text Cite

Efficient parametric yield estimation of analog/mixed-signal circuits via Bayesian model fusion

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · January 1, 2012 Parametric yield estimation is one of the most critical-yet-challenging tasks for designing and verifying nanoscale analog and mixed-signal circuits. In this paper, we propose a novel Bayesian model fusion (BMF) technique for efficient parametric yield est ... Full text Cite

Post-silicon performance modeling and tuning of analog/mixed-signal circuits via bayesian model fusion

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · January 1, 2012 Post-silicon tuning has recently emerged as an important technique to combat large-scale uncertainties (e.g., process variation, device modeling errors, etc) for today's nanoscale circuits. This talk presents a novel Bayesian Model Fusion (BMF) technique f ... Full text Cite

Test cost reduction through performance prediction using virtual probe

Conference Proceedings International Test Conference · December 1, 2011 The virtual probe (VP) technique, based on recent breakthroughs in compressed sensing, has demonstrated its ability for accurate prediction of spatial variations from a small set of measurement data. In this paper, we explore its application to cost reduct ... Full text Cite

Toward efficient spatial variation decomposition via sparse regression

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · December 1, 2011 In this paper, we propose a new technique to accurately decompose process variation into two different components: (1) spatially correlated variation, and (2) uncorrelated random variation. Such variation decomposition is important to identify systematic v ... Full text Cite

Formal verification of phase-locked loops using reachability analysis and continuization

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · December 1, 2011 We present an approach for verifying locking of charge-pump phase-locked loops by performing reachability analysis on a behavioral model of the circuit. Bounded uncertain parameters in the behavioral model make it possible to represent all possible behavio ... Full text Cite

Indirect phase noise sensing for self-healing voltage controlled oscillators

Conference Proceedings of the Custom Integrated Circuits Conference · November 9, 2011 The push for higher performance analog/RF circuits in scaled CMOS necessitates self-healing via post-manufacturing tuning. A major challenge with self-healing systems is the efficient design of on-chip sensors that capture the performance of interest. This ... Full text Cite

Bridging design and manufacture of analog/mixed-signal circuits in advanced CMOS

Conference Digest of Technical Papers Symposium on VLSI Technology · September 16, 2011 We present device and circuit characterization resulting from technology/design co-development to improve the design and manufacture of analog/mixed-signal (AMS) circuits in processors. We introduce I D-based MOSFET transconductance measurements ... Cite

Rethinking memory redundancy: Optimal bit cell repair for maximum-information storage

Conference Proceedings Design Automation Conference · September 16, 2011 SRAM design has been a major challenge for nanoscale manufacturing technology. We propose a new bit cell repair scheme for designing maximum-information memory system (MIMS). Unlike the traditional memory repair that attempts to replace all failed bit cell ... Cite

Efficient SRAM failure rate prediction via Gibbs sampling

Conference Proceedings Design Automation Conference · January 1, 2011 Statistical analysis of SRAM has emerged as a challenging issue because the failure rate of SRAM cells is extremely small. In this paper, we develop an efficient importance sampling algorithm to capture the rare failure event of SRAM cells. In particular, ... Full text Cite

Efficient incremental analysis of on-chip power grid via sparse approximation

Conference Proceedings Design Automation Conference · January 1, 2011 In this paper, a new sparse approximation technique is proposed for incremental power grid analysis. Our proposed method is motivated by the observation that when a power grid network is locally updated during circuit design, its response changes locally a ... Full text Cite

A 130nm CMOS direct conversion transmitter for WCDMA

Conference Icsict 2010 2010 10th IEEE International Conference on Solid State and Integrated Circuit Technology Proceedings · December 1, 2010 A highly integrated 0.13um CMOS direct conversion transmitter front-end for wide-band code division multiple access (WCDMA) is presented. The transmitter delivers +6.8dBm output power while consuming 39mA. The overall gain can be programmed in 6dB steps ov ... Full text Cite

Bayesian Virtual Probe: Minimizing variation characterizationcost for nanoscale IC technologies via Bayesian inference

Conference Proceedings Design Automation Conference · September 7, 2010 The expensive cost of testing and characterizing parametric variations is one of the most critical issues for today's nanoscale manufacturing process. In this paper, we propose a new technique, referred to as Bayesian Virtual Probe (BVP), to efficiently me ... Full text Cite

Toward efficient large-scale performance modeling of integrated circuits via multi-mode/multi-corner sparse regression

Conference Proceedings Design Automation Conference · September 7, 2010 In this paper, we propose a novel multi-mode/multi-corner sparse regression (MSR) algorithm to build large-scale performance models of integrated circuits at multiple working modes and environmental corners. Our goal is to efficiently extract multiple perf ... Full text Cite

Maximum-information storage system: Concept, implementation and application

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · January 1, 2010 The aggressive technology scaling has made it increasingly difficult to design high-performance, high-density SRAM circuits. In this paper, we propose a new SRAM design methodology that is referred to as maximum-information storage system (MISS). Unlike mo ... Full text Cite

Multi-wafer virtual probe: Minimum-cost variation characterization by exploring wafer-to-wafer correlation

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · January 1, 2010 In this paper, we propose a new technique, referred to as MultiWafer Virtual Probe (MVP) to efficiently model wafer-level spatial variations for nanoscale integrated circuits. Towards this goal, a novel Bayesian inference is derived to extract a shared mod ... Full text Cite

Large-scale analog/RF performance modeling by statistical regression

Conference Asicon 2009 Proceedings 2009 8th IEEE International Conference on ASIC · December 1, 2009 In this paper, we introduce several large-scale modeling techniques to analyze the high-dimensional, strongly-nonlinear performance variability observed in nanoscale manufacturing technologies. Our goal is to solve a large number of (e.g., 1044- ... Full text Cite

Virtual probe: A statistically optimal framework for minimum-cost silicon characterization of nanoscale integrated circuits

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · December 1, 2009 In this paper, we propose a new technique, referred to as virtual probe (VP), to efficiently measure, characterize and monitor both inter-die and spatially-correlated intra-die variations in nanoscale manufacturing process. VP exploits recent breakthroughs ... Cite

Surface-potential-based MOSFET models with introduction to PSP

Conference 2009 IEEE 10th Annual Wireless and Microwave Technology Conference Wamicon 2009 · November 18, 2009 We review compact modeling techniques that enable a surface-potential-based approach to modeling MOS transistors. These include symmetric linearization method, an analytical approximation of surface potential and surface-potential-based extrinsic device mo ... Full text Cite

Finding deterministic solution from underdetermined equation: Large-scale performance modeling by least angle regression

Conference Proceedings Design Automation Conference · November 10, 2009 The aggressive scaling of IC technology results in highdimensional, strongly-nonlinear performance variability that cannot be efficiently captured by traditional modeling techniques. In this paper, we adapt a novel L 1-norm regularization method ... Cite

Efficient design-specific worst-case corner extraction for integrated circuits

Conference Proceedings Design Automation Conference · November 10, 2009 While statistical analysis has been considered as an important tool for nanoscale integrated circuit design, many IC designers would like to know the design-specific worst-case corners for circuit debugging and failure diagnosis. In this paper, we propose ... Cite

Parameter extracttion for the PSP MOSFET model by the combination of genetic and levenberg-marquardt algorithms

Conference IEEE International Conference on Microelectronic Test Structures · July 15, 2009 Based on the combination of the genetic and Levenberg-Marquardt algorithms, a new method is developed to perform both local and global parameter extraction for the PSP MOSFET model. It has been successfully used to extract parameter sets for a 65-nm techno ... Full text Cite

Improved parameter extraction procedure for PSP-based MOS varactor model

Conference IEEE International Conference on Microelectronic Test Structures · July 15, 2009 We present an improved procedure for extracting parasitic capacitance parameters and gate current parameters for MOSYAR, the industry standard MOS varactor model. Our technique is verified against measured data from three technology nodes (180 nm, 130 nm a ... Full text Cite

Efficient statistical analysis of read timing failures in sram circuits

Conference Proceedings of the 10th International Symposium on Quality Electronic Design Isqed 2009 · July 8, 2009 A system-level statistical analysis methodology is described that captures the impact of inter- and intra-die process variations for read timing failures in SRAM circuit blocks. Unlike existing approaches that focus on cell-level performance metrics for is ... Full text Cite

The new CMC standard compact MOS model PSP: Advantages for RF applications

Conference IEEE Journal of Solid State Circuits · May 1, 2009 The surface-potential-based compact MOS model PSP is reviewed with special emphasis to features of interest to analog and RF designers. Various aspects of the model are discussed, such as Gummel symmetry, capacitance reciprocity at $VDS = 0 V, p ... Full text Cite

SRAM parametric failure analysis

Conference Proceedings Design Automation Conference · January 1, 2009 With aggressive technology scaling, SRAM design has been seriously challenged by the difficulties in analyzing rare failure events. In this paper we propose to create statistical performance models with accuracy sufficient to facilitate probability extract ... Full text Cite

Mismatch analysis and statistical design at 65 nm and below

Conference Proceedings of the Custom Integrated Circuits Conference · December 26, 2008 Transistor sizing to control random mismatch is investigated. Input offset voltage of 65nm bulk CMOS SRAM sense amplifiers are measured to analyze NMOS and PMOS threshold voltage (Vtn, Vtp) variation effects and compare them with statistical models and Pel ... Full text Cite

Variation-tolerant SRAM sense-amplifier timing using configurable replica bitlines

Conference Proceedings of the Custom Integrated Circuits Conference · December 26, 2008 A configurable replica bitline (cRBL) technique for controlling sense-amplifier enable (SAE) timing for small-swing bitline SRAMs is described. Post-silicon selection of a subset of replica bitline driver cells from a statistically designed pool of cells f ... Full text Cite

A nonlinear body resistance model for accurate PD/SOI technology characterization

Conference Proceedings IEEE International SOI Conference · December 24, 2008 We report a bias-dependent, nonlinear body resistance model suitable for accurate characterization of PD/SOI technology. This model is implemented in the surface potential based SOI MOSFET compact model PSP-SOI and experimentally verified for 65 nm PD/SOI ... Full text Cite

(Invited) the new CMC standard compact MOS model PSP: Advantages for RF applications

Conference Digest of Papers IEEE Radio Frequency Integrated Circuits Symposium · September 22, 2008 First the surface-potential-based compact MOS model, PSP, is introduced. After a discussion of the general advantages of this model, it is benchmarked against measurements from the 45 nm technology node. Finally, we zoom in on the modeling in PSP of two ef ... Full text Cite

Statistical regression for efficient high-dimensional modeling of analog and mixed-signal performance variations

Conference Proceedings Design Automation Conference · September 17, 2008 The continuous technology scaling brings about high-dimensional performance variations that cannot be easily captured by the traditional response surface modeling. In this paper we propose a new statistical regression (STAR) technique that applies a novel ... Full text Cite

Projection-based piecewise-linear response surface modeling for strongly nonlinear VLSI performance variations

Conference Proceedings of the 9th International Symposium on Quality Electronic Design Isqed 2008 · August 25, 2008 Large-scale process fluctuations (particularly random device mismatches) at nanoscale technologies bring about high-dimensional strongly nonlinear performance variations that cannot be accurately captured by linear or quadratic response surface models. In ... Full text Cite

Defining statistical timing sensitivity for logic circuits with large-scale process and environmental variations

Conference IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems · June 1, 2008 The large-scale process and environmental variations for today's nanoscale ICs require statistical approaches for timing analysis and optimization. In this paper, we demonstrate why the traditional concept of slack and critical path becomes ineffective und ... Full text Cite

Adaptive post-silicon tuning for analog circuits: Concept, analysis and optimization

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · December 1, 2007 The well-known Pelgrom model [14] has demonstrated that the variation between two devices on the same die due to random mismatch is inversely proportional to the square root of the device area: σ ∼ 1/sqrt(Area). Based on the Pelgrom model, analog devices a ... Full text Cite

Benchmarking the PSP compact model for MOS transistors

Conference IEEE International Conference on Microelectronic Test Structures · September 27, 2007 Recently, the PSP model was selected as the first surface-potential-based industry standard compact MOSFET model. This work presents the results of several qualitative "benchmark" tests that over the last two years were used to verify the physical behavior ... Full text Cite

Parameterized macromodeling for analog system-level design exploration

Conference Proceedings Design Automation Conference · August 2, 2007 In this paper we propose a novel parameterized macromodeling technique for analog circuits. Unlike traditional macromodels that are only extracted for a small variation space, our proposed approach captures a significantly larger analog design space to fac ... Full text Cite

Efficient parametric yield extraction for multiple correlated non-normal performance distributions of analog/RF circuits

Conference Proceedings Design Automation Conference · August 2, 2007 In this paper we propose an efficient numerical algorithm to estimate the parametric yield of analog/RF circuits with consideration of large-scale process variations. Unlike many traditional approaches that assume Normal performance distributions, the prop ... Full text Cite

PSP-SOI: A surface potential based compact model of partially depleted SOI MOSFETs

Conference Proceedings of the Custom Integrated Circuits Conference · January 1, 2007 This paper reports recent progress on partially depleted (PD) SOI modeling using a surface potential based approach. The new model, called PSP-SOI, Is formulated within the framework of the latest Industry standard bulk MOSFET model PSP. In addition to Its ... Full text Cite

Theory and modeling techniques used in the PSP model

Conference 2006 Nsti Nanotechnology Conference and Trade Show Nsti Nanotech 2006 Technical Proceedings · December 8, 2006 This paper describes theoretical foundation and details of the new compact modeling techniques used in the advanced surface-potential-based compact MOSFET model PSP, jointly developed by the Pennsylvania State University and Philips Research. Specific topi ... Cite

Active on-die suppression of power supply noise

Conference Proceedings of the Custom Integrated Circuits Conference · December 1, 2006 An active on-chip circuit is demonstrated in 130nm CMOS for the suppression of on-chip power supply noise due to power distribution resonance. Testchip measurement results indicate up to 40% reduction in power supply noise during clock/power gating at a 2% ... Full text Cite

Architecture-aware FPGA placement using metric embedding

Conference Proceedings Design Automation Conference · January 1, 2006 Since performance on FPGAs is dominated by the routing architecture rather than wirelength, we propose a new ar-chitecture-aware approach to initial FPGA placement that models the relationship between performance and the routing grid, using concepts from g ... Full text Cite

Projection-based statistical analysis of full-chip leakage power with non-log-normal distributions

Conference Proceedings Design Automation Conference · January 1, 2006 In this paper we propose a novel projection-based algorithm to estimate the full-chip leakage power with consideration of both inter-die and intra-die process variations. Unlike many traditional approaches that rely on log-Normal approximations, the propos ... Full text Cite

Projection-based performance modeling for inter/intra-die variations

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · December 1, 2005 Large-scale process fluctuations in nano-scale IC technologies suggest applying high-order (e.g., quadratic) response surface models to capture the circuit performance variations. Fitting such models requires significantly more simulation samples and solvi ... Full text Cite

OPERA: Optimization with ellipsoidal uncertainty for robust analog IC design

Conference Proceedings Design Automation Conference · December 1, 2005 As the design-manufacturing interface becomes increasingly complicated with IC technology scaling, the corresponding process variability poses great challenges for nanoscale analog/RF design. Design optimization based on the enumeration of process corners ... Cite

Modeling interconnect variability using efficient parametric model order reduction

Conference Proceedings Design Automation and Test in Europe Date 05 · December 1, 2005 Assessing IC manufacturing process fluctuations and their impacts on IC interconnect performance has become unavoidable for modern DSM designs. However, the construction of parametric interconnect models is often hampered by the rapid increase in computati ... Full text Cite

Performance-centering optimization for system-level analog design exploration

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · January 1, 2005 In this paper we propose a novel analog design optimization methodology to address two key aspects of top-down system-level design: (1) how to optimally compare and select analog system architectures in the early phases of design; and (2) how to hierarchic ... Full text Cite

SP-SOI: A third generation surface potential based compact SOI MOSFET model

Conference Proceedings of the Custom Integrated Circuits Conference · January 1, 2005 We report the first SOI MOSFET model that takes advantage of the recent progress in bulk MOSFET modeling. The surface-potential-based model is implemented without iterative loops, and includes physical modeling of the moderate inversion region and all smal ... Full text Cite

Unified non-quasi-static MOSFET model for large-signal and small-signal simulations

Conference Proceedings of the Custom Integrated Circuits Conference · January 1, 2005 The spline-collocation-based non-quasi-static model is extended to include small-geometry effects and to enable both small-signal and large-signal simulations. The new NQS model has been implemented into circuit simulators using both SP and PSP models and ... Full text Cite

Correlation-aware statistical timing analysis with non-gaussian delay distributions

Conference Proceedings Design Automation Conference · January 1, 2005 Process variations have a growing impact on circuit performance for today's integrated circuit (IC) technologies. The Non-Gaussian delay distributions as well as the correlations among delays make statistical timing analysis more challenging than ever. In ... Full text Cite

Defining statistical sensitivity for timing optimization of logic circuits with large-scale process and environmental variations

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · January 1, 2005 The large-scale process and environmental variations for today's nanoscale ICs are requiring statistical approaches for timing analysis and optimization. Significant research has been recently focused on developing new statistical timing analysis algorithm ... Full text Cite

Asymptotic probability extraction for non-normal distributions of circuit performance

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · December 1, 2004 While process variations are becoming more significant with each new IC technology generation, they are often modeled via linear regression models so that the resulting performance variations can be captured via Normal distributions. Nonlinear (e.g. quadra ... Cite

Robust analog/RF circuit design with projection-based posynomial modeling

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers Iccad · December 1, 2004 In this paper we propose a RObust Analog Design tool (ROAD) for post-tuning analog/RF circuits. Starting from an initial design derived from hand analysis or analog circuit synthesis based on simplified models, ROAD extracts accurate posynomial performance ... Cite

STAC: Statistical timing analysis with correlation

Conference Proceedings Design Automation Conference · September 20, 2004 Current technology trends have led to the growing impact of both inter-die and intra-die process variations on circuit performance. While it is imperative to model parameter variations for sub-100nm technologies to produce an upper bound prediction on timi ... Cite

A frequency relaxation approach for analog/RF system-level simulation

Conference Proceedings Design Automation Conference · January 1, 2004 The increasing complexity of today's mixed-signal integrated circuits necessitates both top-down and bottom-up system-level verification. Time-domain state-space modeling and simulation approaches have been successfully applied for such purposes (e.g. Simu ... Full text Cite

A Hybrid Approach to Nonlinear Macromodel Generation for Time-Varying Analog Circuits

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers · December 26, 2003 Modeling frequency-dependent nonlinear characteristics of complex analog blocks and subsystems is critical for enabling efficient verification of mixed-signal system designs. Recent progress has been made for constructing such macromodels, however, their a ... Cite

Noise macromodel for radio frequency integrated circuits

Conference Proceedings Design Automation and Test in Europe Date · December 1, 2003 Noise performance is a critical analog and RF circuit design constraint, and can impact the selection of the IC system-level architecture. It is therefore imperative that some model of the noise is represented at the highest levels of abstraction during th ... Full text Cite

Noise macromodel for radio frequency integrated circuits

A frequency separation macromodel for system-level simulation of RF circuits

Conference Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC · January 1, 2003 In this paper, we propose a frequency-separation methodology to generate system-level macromodels for analog and RF circuits. The proposed macromodels are similar in form to those based on Volterra kernel calculations, but are much simpler in terms of char ... Full text Cite

Analog and RF circuit macromodels for system-level analysis

Conference Proceedings Design Automation Conference · January 1, 2003 Design and validation of mixed-signal integrated systems require system-level model abstractions. Generalized Volterra series based models have been successfully applied for analog and RF component macromodels, but their complexity can sometimes limit thei ... Full text Cite

Wavelet method for high-speed clock tree simulation

Conference Proceedings IEEE International Symposium on Circuits and Systems · January 1, 2002 In this paper, we propose a fast wavelet collocation algorithm for high-speed clock tree simulation. Taking advantage of the specific structure of clock trees and the superior computational property of wavelets, the proposed algorithm presents the followin ... Cite

A wavelet balance approach for steady-state analysis of nonlinear circuits

Conference Iscas 2001 2001 IEEE International Symposium on Circuits and Systems Conference Proceedings · December 1, 2001 In this paper, a novel wavelet balance method is proposed for steady-state analysis of nonlinear circuits. The proposed method presents several merits compared with those conventional frequency domain techniques, First, it has a high convergence rate. Seco ... Full text Cite

Behavioral modeling of analog circuits by wavelet collocation method

Conference IEEE ACM International Conference on Computer Aided Design Digest of Technical Papers · January 1, 2001 In this paper, we develop a wavelet collocation method with nonlinear companding for behavioral modeling of analog circuits. To construct the behavioral models, the circuit is first partitioned into building blocks and the input-output function of each blo ... Cite

Accurate chip scale topography modeling in O(n) run time

Conference International Conference on Simulation of Semiconductor Processes and Devices SISPAD · January 1, 1996 Currently, semiconductor manufacturing topography models for design and process optimization can investigate only a tiny portion of a die at a given time. Therefore, important coupling effects between areas are ignored. As interconnect capacitance and resi ... Full text Cite