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Author: Yu Ben Publisher: ISBN: Category : Languages : en Pages : 208
Book Description
Semiconductor technology has gone through several decades of aggressive scaling. The ever shrinking size of both transistors and interconnects is necessitating the interaction between the circuit designers and the foundries that fabricate the IC products. In particular, the designers must take into account the impact of the process variability early in the design stage. This includes both the verification and optimization of the circuit with statistical models characterizing the process variability. This thesis advances three frontiers in the variability-aware design flow. Yield estimation is a crucial but expensive verification step in circuit design. Existing methods either suffer from computationally intensive rare event probability calculation, or exhibit poor stability. We investigate the problem by combining partial least squares (PLS) regression, a dimension-reduction technique, with importance sampling, a variance-reduction technique. The simulation results show that the method is able to improve the convergence speed by at least an order of magnitude over existing fast simulation methods, and four orders of magnitude faster than Monte Carlo. In addition to PLS-preconditioned importance sampling, several other methods are also investigated, and their properties are compared. For a quicker verification of the robustness of the circuit, circuit designers often simulate the circuit using corner models. Current corner models are extracted using single transistor performances and cannot incorporate local variability. These facts limit the usage of corner models in deep sub-micron devices and analog applications. We propose to extract the customized corners using PLS regression. The method is tested using ISCAS'85 benchmark circuits. Both the probability density function and cumulative distribution function of the circuit performance predicted by the customized corners agree with Monte Carlo simulation, while delivering two orders of magnitude computational acceleration. The last frontier concerns robust circuit optimization. Most of the existing methods can only deal with a pessimistic worst-case problem. We choose to solve the ideal yield-constrained circuit optimization problem. To this end, we introduce the idea of robust convex approximation to design automation for the first time. Based on the convex approximation, we propose a sequential method to accommodate a realistic, hierarchical variability model. A simple line-search as an outer-loop algorithm is used to control the output the method. The optimization result shows that the proposed method is capable of handling circuits of thousands of gates without performance penalties due to overdesign.
Author: Yu Ben Publisher: ISBN: Category : Languages : en Pages : 208
Book Description
Semiconductor technology has gone through several decades of aggressive scaling. The ever shrinking size of both transistors and interconnects is necessitating the interaction between the circuit designers and the foundries that fabricate the IC products. In particular, the designers must take into account the impact of the process variability early in the design stage. This includes both the verification and optimization of the circuit with statistical models characterizing the process variability. This thesis advances three frontiers in the variability-aware design flow. Yield estimation is a crucial but expensive verification step in circuit design. Existing methods either suffer from computationally intensive rare event probability calculation, or exhibit poor stability. We investigate the problem by combining partial least squares (PLS) regression, a dimension-reduction technique, with importance sampling, a variance-reduction technique. The simulation results show that the method is able to improve the convergence speed by at least an order of magnitude over existing fast simulation methods, and four orders of magnitude faster than Monte Carlo. In addition to PLS-preconditioned importance sampling, several other methods are also investigated, and their properties are compared. For a quicker verification of the robustness of the circuit, circuit designers often simulate the circuit using corner models. Current corner models are extracted using single transistor performances and cannot incorporate local variability. These facts limit the usage of corner models in deep sub-micron devices and analog applications. We propose to extract the customized corners using PLS regression. The method is tested using ISCAS'85 benchmark circuits. Both the probability density function and cumulative distribution function of the circuit performance predicted by the customized corners agree with Monte Carlo simulation, while delivering two orders of magnitude computational acceleration. The last frontier concerns robust circuit optimization. Most of the existing methods can only deal with a pessimistic worst-case problem. We choose to solve the ideal yield-constrained circuit optimization problem. To this end, we introduce the idea of robust convex approximation to design automation for the first time. Based on the convex approximation, we propose a sequential method to accommodate a realistic, hierarchical variability model. A simple line-search as an outer-loop algorithm is used to control the output the method. The optimization result shows that the proposed method is capable of handling circuits of thousands of gates without performance penalties due to overdesign.
Author: Jian Cheng Zhang Publisher: Springer Science & Business Media ISBN: 1461522250 Category : Technology & Engineering Languages : en Pages : 244
Book Description
Traditionally, Computer Aided Design (CAD) tools have been used to create the nominal design of an integrated circuit (IC), such that the circuit nominal response meets the desired performance specifications. In reality, however, due to the disturbances ofthe IC manufacturing process, the actual performancesof the mass produced chips are different than those for the nominal design. Even if the manufacturing process were tightly controlled, so that there were little variations across the chips manufactured, the environmentalchanges (e. g. those oftemperature, supply voltages, etc. ) would alsomakethe circuit performances vary during the circuit life span. Process-related performance variations may lead to low manufacturing yield, and unacceptable product quality. For these reasons, statistical circuit design techniques are required to design the circuit parameters, taking the statistical process variations into account. This book deals with some theoretical and practical aspects of IC statistical design, and emphasizes how they differ from those for discrete circuits. It de scribes a spectrum of different statistical design problems, such as parametric yield optimization, generalized on-target design, variability minimization, per formance tunning, and worst-case design. The main emphasis of the presen tation is placed on the principles and practical solutions for performance vari ability minimization. It is hoped that the book may serve as an introductory reference material for various groups of IC designers, and the methodologies described will help them enhance the circuit quality and manufacturability. The book containsseven chapters.
Author: Stephan Weber Publisher: CRC Press ISBN: 1000794091 Category : Technology & Engineering Languages : en Pages : 638
Book Description
Circuit Design = Science + Art! Designers need a skilled "gut feeling" about circuits and related analytical techniques, plus creativity, to solve all problems and to adhere to the specifications, the written and the unwritten ones. You must anticipate a large number of influences, like temperature effects, supply voltages changes, offset voltages, layout parasitics, and numerous kinds of technology variations to end up with a circuit that works. This is challenging for analog, custom-digital, mixed-signal or RF circuits, and often researching new design methods in relevant journals, conference proceedings and design tools unfortunately gives the impression that just a "wild bunch" of "advanced techniques" exist. On the other hand, state-of-the-art tools nowadays indeed offer a good cockpit to steer the design flow, which include clever statistical methods and optimization techniques.Actually, this almost presents a second breakthrough, like the introduction of circuit simulators 40 years ago! Users can now conveniently analyse all the problems (discover, quantify, verify), and even exploit them, for example for optimization purposes. Most designers are caught up on everyday problems, so we fit that "wild bunch" into a systematic approach for variation-aware design, a designer's field guide and more. That is where this book can help! Circuit Design: Anticipate, Analyze, Exploit Variations starts with best-practise manual methods and links them tightly to up-to-date automation algorithms. We provide many tractable examples and explain key techniques you have to know. We then enable you to select and setup suitable methods for each design task - knowing their prerequisites, advantages and, as too often overlooked, their limitations as well. The good thing with computers is that you yourself can often verify amazing things with little effort, and you can use software not only to your direct advantage in solving a specific problem, but also for becoming a better skilled, more experienced engineer. Unfortunately, EDA design environments are not good at all to learn about advanced numerics. So with this book we also provide two apps for learning about statistic and optimization directly with circuit-related examples, and in real-time so without the long simulation times. This helps to develop a healthy statistical gut feeling for circuit design. The book is written for engineers, students in engineering and CAD / methodology experts. Readers should have some background in standard design techniques like entering a design in a schematic capture and simulating it, and also know about major technology aspects.
Author: Michael Orshansky Publisher: Springer Science & Business Media ISBN: 0387690115 Category : Technology & Engineering Languages : en Pages : 319
Book Description
Design for Manufacturability and Statistical Design: A Comprehensive Approach presents a comprehensive overview of methods that need to be mastered in understanding state-of-the-art design for manufacturability and statistical design methodologies. Broadly, design for manufacturability is a set of techniques that attempt to fix the systematic sources of variability, such as those due to photolithography and CMP. Statistical design, on the other hand, deals with the random sources of variability. Both paradigms operate within a common framework, and their joint comprehensive treatment is one of the objectives of this book and an important differentation.
Author: Trent McConaghy Publisher: Springer Science & Business Media ISBN: 1461422698 Category : Technology & Engineering Languages : en Pages : 198
Book Description
This book targets custom IC designers who are encountering variation issues in their designs, especially for modern process nodes at 45nm and below, such as statistical process variations, environmental variations, and layout effects. It teaches them the state-of-the-art in Variation-Aware Design tools, which help the designer to analyze quickly the variation effects, identify the problems, and fix the problems. Furthermore, this book describes the algorithms and algorithm behavior/performance/limitations, which is of use to designers considering these tools, designers using these tools, CAD researchers, and CAD managers.
Author: Erik Larsson Publisher: Springer Science & Business Media ISBN: 9781402032073 Category : Technology & Engineering Languages : en Pages : 418
Book Description
Testing of Integrated Circuits is important to ensure the production of fault-free chips. However, testing is becoming cumbersome and expensive due to the increasing complexity of these ICs. Technology development has made it possible to produce chips where a complete system, with an enormous transistor count, operating at a high clock frequency, is placed on a single die - SOC (System-on-Chip). The device size miniaturization leads to new fault types, the increasing clock frequencies enforces testing for timing faults, and the increasing transistor count results in a higher number of possible fault sites. Testing must handle all these new challenges in an efficient manner having a global system perspective. Test design is applied to make a system testable. In a modular core-based environment where blocks of reusable logic, the so called cores, are integrated to a system, test design for each core include: test method selection, test data (stimuli and responses) generation (ATPG), definition of test data storage and partitioning [off-chip as ATE (Automatic Test Equipment) and/or on-chip as BIST (Built-In Self-Test)], wrapper selection and design (IEEE std 1500), TAM (test access mechanism) design, and test scheduling minimizing a cost function whilst considering limitations and constraint. A system test design perspective that takes all the issues above into account is required in order to develop a globally optimized solution. SOC test design and its optimization is the topic of this book. It gives an introduction to testing, describes the problems related to SOC testing, discusses the modeling granularity and the implementation into EDA (electronic design automation) tools. The book is divided into three sections: i) test concepts, ii) SOC design for test, and iii) SOC test applications. The first part covers an introduction into test problems including faults, fault types, design-flow, design-for-test techniques such as scan-testing and Boundary Scan. The second part of the book discusses SOC related problems such as system modeling, test conflicts, power consumption, test access mechanism design, test scheduling and defect-oriented scheduling. Finally, the third part focuses on SOC applications, such as integrated test scheduling and TAM design, defect-oriented scheduling, and integrating test design with the core selection process.
Author: Christopher Michael Publisher: Springer Science & Business Media ISBN: 9780792392996 Category : Computers Languages : en Pages : 220
Book Description
As MOS devices are scaled to meet increasingly demanding circuit specifications, process variations have a greater effect on the reliability of circuit performance. For this reason, statistical techniques are required to design integrated circuits with maximum yield. Statistical Modeling for Computer-Aided Design of MOS VLSI Circuits describes a statistical circuit simulation and optimization environment for VLSI circuit designers. The first step toward accomplishing statistical circuit design and optimization is the development of an accurate CAD tool capable of performing statistical simulation. This tool must be based on a statistical model which comprehends the effect of device and circuit characteristics, such as device size, bias, and circuit layout, which are under the control of the circuit designer on the variability of circuit performance. The distinctive feature of the CAD tool described in this book is its ability to accurately model and simulate the effect in both intra- and inter-die process variability on analog/digital circuits, accounting for the effects of the aforementioned device and circuit characteristics. Statistical Modeling for Computer-Aided Design of MOS VLSI Circuits serves as an excellent reference for those working in the field, and may be used as the text for an advanced course on the subject.
Author: Yu Ben
Author: Yu Ben
Author: Jian Cheng Zhang
Author: Daniel D. Alexander
Author: Stephan Weber
Author: Michael Orshansky
Author: Trent McConaghy
Author: Erik Larsson
Author: Christopher Michael
Author: Curtis Lemay Pastor
Author: Andrzej J. Strojwas