Duo Li

Bio: Duo Li is an academic researcher from University of California, Riverside. The author has contributed to research in topics: Model order reduction & Speedup. The author has an hindex of 7, co-authored 14 publications receiving 139 citations. Previous affiliations of Duo Li include Synopsys.

ETBR: extended truncated balanced realization method for on-chip power grid network analysis

Abstract: In this paper, we present a novel simulation approach for power grid network analysis. The new approach, called ETBR for extended truncated balanced realization, is based on model order reduction techniques to reduce the circuit matrices before the simulation. Different from the (improved) extended Krylov subspace methods EKS/IEKS [15, 2], ETBR performs fast truncated balanced realization on response Grammian to reduce the original system with the similar computation costs of EKS. ETBR also avoids the adverse explicit moment representation of the input signals. Instead, it uses spectrum representation of input signals by fast Fourier transformation. As a result, ETBR is more flexible for different types of input sources and can better capture the high frequency contents than EKS, and this leads to more accurate results especially for fast changing input signals. Experimental results on a number of large networks (up to one million nodes) show that, given the same order of the reduced model, ETBR is indeed more accurate than the EKS method especially for input sources rich in high-frequency components. ETBR also shows similar computation costs of EKS and less memory consumption than EKS.

Parameterized architecture-level dynamic thermal models for multicore microprocessors

Abstract: In this article, we propose a new architecture-level parameterized dynamic thermal behavioral modeling algorithm for emerging thermal-related design and optimization problems for high-performance multicore microprocessor design We propose a new approach, called ParThermPOF, to build the parameterized thermal performance models from the given accurate architecture thermal and power information The new method can include a number of variable parameters such as the locations of thermal sensors in a heat sink, different components (heat sink, heat spreader, core, cache, etc), thermal conductivity of heat sink materials, etc The method consists of two steps: first, a response surface method based on low-order polynomials is applied to build the parameterized models at each time point for all the given sampling nodes in the parameter space Second, an improved Generalized Pencil-Of-Function (GPOF) method is employed to build the transfer-function-based behavioral models for each time-varying coefficient of the polynomials generated in the first step Experimental results on a practical quad-core microprocessor show that the generated parameterized thermal model matches the given data very well The compact models by ParThermPOF offer two order of magnitudes speedup over the commercial thermal analysis tool FloTHERM on the given examples ParThermPOF is very suitable for design space exploration and optimization where both time and system parameters need to be considered

Composable thermal modeling and simulation for architecture-level thermal designs of multicore microprocessors

Abstract: Efficient temperature estimation is vital for designing thermally efficient, lower power and robust integrated circuits in nanometer regime. Thermal simulation based on the detailed thermal structures no longer meets the demanding tasks for efficient design space exploration. The compact and composable model-based simulation provides a viable solution to this difficult problem. However, building such thermal models from detailed thermal structures was not well addressed in the past. In this article, we propose a new compact thermal modeling technique, called ThermComp, standing for thermal modeling with composable modules. ThermComp can be used for fast thermal design space exploration for multicore microprocessors. The new approach builds the composable model from detailed structures for each basic module using the finite difference method and reduces the model complexity by the sampling-based model order reduction technique. These composable models are then used to assemble different multicore architecture thermal models and realized into SPICE-like netlists. The resulting thermal models can be simulated by the general circuit simulator SPICE. ThermComp tries to preserve the accuracy of fine-grained models with the speed of coarse-grained models. Experimental results on a number of multicore microprocessor architectures show the new approach can easily build accurate thermal systems from compact composable models for fast architecture thermal analysis and optimization and is much faster than the existing HotSpot method with similar accuracy.

General Parameterized Thermal Modeling for High-Performance Microprocessor Design

Abstract: This paper proposes a new parameterized dynamic thermal modeling algorithm for emerging thermal-aware design and optimization for high-performance microprocessor design at architecture and package levels. Compared with existing behavioral thermal modeling algorithms, the proposed method can build the compact models from more general transient power and temperature waveforms used as training data. Such an approach can make the modeling process much easier and less restrictive than before and, thus, more amenable for practical measured data. The new method, called ParThermSID, consists of two steps. First, the response surface method based on second-order polynomials is applied to build the parameterized models at each time point for all of the given sampling nodes in the parameter space. Second, an improved subspace system identification method, called ThermSID, is employed to build the discrete state space models, by construction of the Hankel matrix and state space realization, for each time-varying coefficient of the polynomials generated in the first step. To overcome the overfitting problems of the subspace method, the new method employs an overfitting mitigation technique to improve model accuracy and predictive ability. Experimental results on a practical quad-core microprocessor show that the generated parameterized thermal model matches the given data very well. The compact models generated by ParThermSID also offer two orders of magnitude speedup over the commercial thermal analysis tool FloTHERM on the given example. The results also show that ThermSID is more accurate than the existing ThermPOF method.

Architecture-Level Thermal Characterization for Multicore Microprocessors

Abstract: This paper investigates a new architecture-level thermal characterization problem from a behavioral modeling perspective to address the emerging thermal related analysis and optimization problems for high-performance multicore microprocessor design. We propose a new approach, called ThermPOF, to build the thermal behavioral models from the measured or simulated thermal and power information at the architecture level. ThermPOF first builds the behavioral thermal model using the generalized pencil-of-function (GPOF) method. Owing to the unique characteristics of transient temperature changes at the chip level, we propose two new schemes to improve the GPOF. First, we apply a logarithmic-scale sampling scheme instead of the traditional linear sampling to better capture the temperature changing behaviors. Second, we modify the extracted thermal impulse response such that the extracted poles from GPOF are guaranteed to be stable without accuracy loss. To further reduce the model size, a Krylov subspace-based reduction method is performed to reduce the order of the models in the state-space form. Experimental results on a real quad-core microprocessor show that generated thermal behavioral models match the given temperature very well.

Digital control of dynamic systems

Abstract: Digital Control Of Dynamic Systems This well-respected, market-leading text discusses the use of digital computers in the real-time control of dynamic systems. The emphasis is on the design of digital controls that achieve good dynamic response and small errors while using signals that are sampled in time and quantized in amplitude. Digital Control of Dynamic Systems (3rd Edition): Franklin ... This well-respected, market-leading text discusses the use of digital computers in the real-time control of dynamic systems. The emphasis is on the design of digital controls that achieve good dynamic response and small errors while using signals that are sampled in time and quantized in amplitude. Digital Control of Dynamic Systems: Gene F. Franklin ... Digital Control of Dynamic Systems, 2nd Edition. Gene F. Franklin, Stanford University. J. David Powell, Stanford University Digital Control of Dynamic Systems, 2nd Edition Pearson This well-respected work discusses the use of digital computers in the real-time control of dynamic systems. The emphasis is on the design of digital controls that achieve good dynamic response and small errors while using signals that are sampled in time and quantized in amplitude. MATLAB statements and problems are thoroughly and carefully integrated throughout the book to offer readers a complete design picture. Digital Control of Dynamic Systems, 3rd Edition ... Digital control of dynamic systems | Gene F. Franklin, J. David Powell, Michael L. Workman | download | B–OK. Download books for free. Find books Digital control of dynamic systems | Gene F. Franklin, J ... Abstract This well-respected work discusses the use of digital computers in the real-time control of dynamic systems. The emphasis is on the design of digital controls that achieve good dynamic... (PDF) Digital Control of Dynamic Systems Digital Control of Dynamic Systems, Addison.pdf There is document Digital Control of Dynamic Systems, Addison.pdfavailable here for reading and downloading. Use the download button below or simple online reader. The file extension PDFand ranks to the Documentscategory. Digital Control of Dynamic Systems, Addison.pdf Download ... Automatic control is the science that develops techniques to steer, guide, control dynamic systems. These systems are built by humans and must perform a specific task. Examples of such dynamic systems are found in biology, physics, robotics, finance, etc. Digital Control means that the control laws are implemented in a digital device, such as a microcontroller or a microprocessor. Introduction to Digital Control of Dynamic Systems And ... The discussions are clear, nomenclature is not hard to follow and there are plenty of worked examples. The book covers discretization effects and design by emulation (i.e. design of continuous-time control system followed by discretization before implementation) which are not to be found on every book on digital control. Amazon.com: Customer reviews: Digital Control of Dynamic ... Find helpful customer reviews and review ratings for Digital Control of Dynamic Systems (3rd Edition) at Amazon.com. Read honest and unbiased product reviews from our users. Amazon.com: Customer reviews: Digital Control of Dynamic ... 1.1.2 Digital control Digital control systems employ a computer as a fundamental component in the controller. The computer typically receives a measurement of the controlled variable, also often receives the reference input, and produces its output using an algorithm. Introduction to Applied Digital Control From the Back Cover This well-respected, marketleading text discusses the use of digital computers in the real-time control of dynamic systems. The emphasis is on the design of digital controls that achieve good dynamic response and small errors while using signals that are sampled in time and quantized in amplitude. Digital Control of Dynamic Systems (3rd Edition) Test Bank `Among the advantages of digital logic for control are the increased flexibility `of the control programs and the decision-making or logic capability of digital `systems, which can be combined with the dynamic control function to meet `other system requirements. `The digital controls studied in this book are for closed-loop (feedback) Every day, eBookDaily adds three new free Kindle books to several different genres, such as Nonfiction, Business & Investing, Mystery & Thriller, Romance, Teens & Young Adult, Children's Books, and others.

Parallel CAD: Algorithm Design and Programming Special Section Call for Papers TODAES: ACM Transactions on Design Automation of Electronic Systems

Abstract: High-performance parallel computer architecture and systems have been improved at a phenomenal rate. In the meantime, VLSI computer-aided design (CAD) software for multibillion-transistor IC design has become increasingly complex and requires prohibitively high computational resources. Recent studies have shown that, numerous CAD problems, with their high computational complexity, can greatly benefit from the fast-increasing parallel computation capabilities. However, parallel programming imposes big challenges for CAD applications. Fully exploiting the computational power of emerging general-purpose and domain-specific multicore/many-core processor systems, calls for fundamental research and engineering practice across every stage of parallel CAD design, from algorithm exploration, programming models, design-time and run-time environment, to CAD applications, such as verification, optimization, and simulation. This journal special section will cover recent progress on parallel CAD research, including algorithm foundations, programming models, parallel architectural-specific optimization, and verification. More specifically, papers with in-depth and extensive coverage of the following topics will be considered, as well as other topics relevant to the design of parallel CAD algorithms and software tools. 1. Parallel algorithm design and specification for CAD applications 2. Parallel programming models and languages of particular use in CAD 3. Runtime support and performance optimization for CAD applications 4. Parallel architecture-specific design and optimization for CAD applications 5. Parallel program debugging and verification techniques particularly relevant for CAD The papers should be submitted via the Manuscript Central website and should adhere to standard ACM TODAES formatting requirements (http://todaes.acm.org/). The page count limit is 25.

A First Course in the Numerical Analysis of Differential Equations: Stiff equations

Abstract: Cambridge University Press. Paperback. Book Condition: New. Paperback. 480 pages. Numerical analysis presents different faces to the world. For mathematicians it is a bona fide mathematical theory with an applicable flavour. For scientists and engineers it is a practical, applied subject, part of the standard repertoire of modelling techniques. For computer scientists it is a theory on the interplay of computer architecture and algorithms for real-number calculations. The tension between these standpoints is the driving force of this book, which presents a rigorous account of the fundamentals of numerical analysis of both ordinary and partial differential equations. The exposition maintains a balance between theoretical, algorithmic and applied aspects. This new edition has been extensively updated, and includes new chapters on emerging subject areas: geometric numerical integration, spectral methods and conjugate gradients. Other topics covered include multistep and Runge-Kutta methods; finite difference and finite elements techniques for the Poisson equation; and a variety of algorithms to solve large, sparse algebraic systems. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback.

An Effective Gray-Box Identification Procedure for Multicore Thermal Modeling

Abstract: Aggressive thermal management is a critical feature for high-end computing platforms, as worst-case thermal budgeting is becoming unaffordable. Reactive thermal management, which sets temperature thresholds to trigger thermal capping actions, is too “near-sighted,” and it may lead to severe performance degradation and thermal overshoots. More aggressive proactive thermal managements minimize performance penalty with smooth optimal control. These techniques require knowledge of thermal models, which have to be accurate and simple to make the controls effective, while keeping their complexity limited. In practice, these models are not provided by manufacturers, and in most cases, they strongly depend on the deployment environment. Hence, procedures to automatically derive thermal models in the field are needed. In this paper, we propose a gray-box procedure to learn a compact and physically consistent model for multicore chips. We leverage the physical consistency of the proposed model to tame the model complexity and to face large quantization noise in measurements. We exploit Output Error structures along with Levenberg–Marquardt and Least Squares optimization algorithms. We tackle the problem in a real-life contest: we developed a complete infrastructure for model building and thermal data collection in the Linux environment, and we tested it on an Intel Nehalem-based server CPU.

System-Level Modeling and Analysis of Thermal Effects in Optical Networks-on-Chip

Abstract: The performance of multiprocessor systems, such as chip multiprocessors (CMPs), is determined not only by individual processor performance, but also by how efficiently the processors collaborate with one another. It is the communication architecture that determines the collaboration efficiency on the hardware side. Optical networks-on-chip (ONoCs) are emerging communication architectures that can potentially offer ultra-high communication bandwidth and low latency to multiprocessor systems. Thermal sensitivity is an intrinsic characteristic of photonic devices used by ONoCs as well as a potential issue. This paper systematically modeled and quantitatively analyzed the thermal effects in ONoCs. We used an 8 × 8 mesh-based ONoC as a case study and evaluated the impacts of thermal effects in the average power efficiency for real MPSoC applications. We revealed three important factors regarding ONoC power efficiency under temperature variations, and proposed several techniques to reduce the temperature sensitivity of ONoCs. These techniques include the optimal initial setting of microresonator resonant wavelength, increasing the 3-dB bandwidth of optical switching elements by parallel coupling multiple microresonators, and the use of passive-routing optical router Crux to minimize the number of switching stages in mesh-based ONoCs. We gave a mathematical analysis of periodically parallel coupling of multiple microresonators and show that the 3-dB bandwidth of optical switching elements can be widened nearly linearly with the ring number. Evaluation results for different real MPSoC applications show that, on the basis of thermal tuning, the optimal device setting improves the average power efficiency by 54% to 1.2 pJ/bit when chip temperature reaches 85 °C. The findings in this paper can help support the further development of this emerging technology.