Variability-driven module selection with joint design time optimization and post-silicon tuning

Abstract—Increasing delay and power variation are significant chal-lenges to the designers as technology scales to the deep sub-micron (DSM) regime. Traditional module selection techniques in high level synthesis use worst case delay/power information to perform the optimization, and therefore may be too pessimistic such that extra resources are used to guarantee design requirements. Parametric yield, which is defined as the probability of the synthesized hardware meeting the performance/power constraints, can be used to guide design space exploration. The para-metric yield can be effectively improved by combining both design-time variation-aware optimization and post silicon tuning techniques (such as adaptive body biasing (ABB)). In this paper, we propose a module selection algorithm that combines design-time optimization with post-silicon tuning (using ABB) to maximize design yield. A variation-aware module selection algorithm based on efficient performance and power yield gradient computation is developed. The post silicon optimization is formulated as an efficient sequential conic program to determine the optimal body bias distribution, which in turn affects design-time module selection. The experiment results show that significant yield can be achieved compared to traditional worst-case driven module selection technique. To the best of our knowledge, this is the first variability-driven high level synthesis technique that considers post-silicon tuning during design time optimization. 1 I

Theory and Applications of Robust Optimization

In this paper we survey the primary research, both theoretical and applied, in the area of Robust Optimization (RO). Our focus is on the computational attractiveness of RO approaches, as well as the modeling power and broad applicability of the methodology. In addition to surveying prominent theoretical results of RO, we also present some recent results linking RO to adaptable models for multi-stage decision-making problems. Finally, we highlight applications of RO across a wide spectrum of domains, including finance, statistics, learning, and various areas of engineering.Comment: 50 page

Reliability and security in low power circuits and systems

With the massive deployment of mobile devices in sensitive areas such as healthcare and defense, hardware reliability and security have become hot research topics in recent years. These topics, although different in definition, are usually correlated. This dissertation offers an in-depth treatment on enhancing the reliability and security of low power circuits and systems. The first part of the dissertation deals with the reliability of sub-threshold designs, which use supply voltage lower than the threshold voltage (Vth) of transistors to reduce power. The exponential relationship between delay and Vth significantly jeopardizes their reliability due to process variation induced timing violations. In order to address this problem, this dissertation proposes a novel selective body biasing scheme. In the first work, the selective body biasing problem is formulated as a linearly constrained statistical optimization model, and the adaptive filtering concept is borrowed from the signal processing community to develop an efficient solution. However, since the adaptive filtering algorithm lacks theoretical justification and guaranteed convergence rate, in the second work, a new approach based on semi-infinite programming with incremental hypercubic sampling is proposed, which demonstrates better solution quality with shorter runtime. The second work deals with the security of low power crypto-processors, equipped with Random Dynamic Voltage Scaling (RDVS), in the presence of Correlation Power Analysis (CPA) attacks. This dissertation firstly demonstrates that the resistance of RDVS to CPA can be undermined by lowering power supply voltage. Then, an alarm circuit is proposed to resist this attack. However, the alarm circuit will lead to potential denial-of-service due to noise-triggered false alarms. A non-zero sum game model is then formulated and the Nash Equilibria is analyzed --Abstract, page iii

Joint design-time and post-silicon optimization for digitally tuned analog circuits,” ICCAD

Abstract-Joint design time and post-silicon optimization for analog circuits has been an open problem in literature because of the complex nature of analog circuit modeling and optimization. In this paper we formulate the co-optimization problem for digitally tuned analog circuits to optimize the parametric yield, subject to power and area constraints. A general optimization framework combing the branch-andbound algorithm and gradient ascent method is proposed. We demonstrate our framework with two examples in high-speed serial link, the transmitter design and the phase-locked-loop (PLL) design. Simulation results show that compared with the design heuristic from analog designers' perspective, joint design-time and post-silicon optimization can improve the yield by up to 47% for transmitter design and up to 56% for PLL design under the same area and power constraints. To the best of the authors' knowledge, this is the first yield-driven analog circuit design technique that optimizes post-silicon tuning together with the design-time optimization

Non-invasive IC tomography using spatial correlations

We introduce a new methodology for post-silicon characterization of the gate-level variations in a manufactured Integrated Circuit (IC). The estimated characteristics are based on the power and the delay measurements that are affected by the process variations. The power (delay) variations are spatially correlated. Thus, there exists a basis in which variations are sparse. The sparse representation suggests using the L1-regularization (the compressive sensing theory). We show how to use the compressive sensing theory to improve post-silicon characterization. We also address the problem by adding spatial constraints directly to the traditional L2-minimization. The proposed methodology is fast, inexpensive, non-invasive, and applicable to legacy designs. Noninvasive IC characterization has a range of emerging applications, including post-silicon optimization, IC identification, and variations' modeling/simulations. The evaluation results on standard benchmark circuits show that, in average, the gate level characteristics estimation accuracy can be improved by more than two times using the proposed methods

Algorithm Engineering in Robust Optimization

Robust optimization is a young and emerging field of research having received a considerable increase of interest over the last decade. In this paper, we argue that the the algorithm engineering methodology fits very well to the field of robust optimization and yields a rewarding new perspective on both the current state of research and open research directions. To this end we go through the algorithm engineering cycle of design and analysis of concepts, development and implementation of algorithms, and theoretical and experimental evaluation. We show that many ideas of algorithm engineering have already been applied in publications on robust optimization. Most work on robust optimization is devoted to analysis of the concepts and the development of algorithms, some papers deal with the evaluation of a particular concept in case studies, and work on comparison of concepts just starts. What is still a drawback in many papers on robustness is the missing link to include the results of the experiments again in the design

DEVELOPMENT OF A SIMPLIFIED, MASS PRODUCIBLE HYBRIDIZED AMBIENT, LOW FREQUENCY, LOW INTENSITY VIBRATION ENERGY SCAVENGER (HALF-LIVES)

Scavenging energy from environmental sources is an active area of research to enable remote sensing and microsystems applications. Furthermore, as energy demands soar, there is a significant need to explore new sources and curb waste. Vibration energy scavenging is one environmental source for remote applications and a candidate for recouping energy wasted by mechanical sources that can be harnessed to monitor and optimize operation of critical infrastructure (e.g. Smart Grid). Current vibration scavengers are limited by volume and ancillary requirements for operation such as control circuitry overhead and battery sources. This dissertation, for the first time, reports a mass producible hybrid energy scavenger system that employs both piezoelectric and electrostatic transduction on a common MEMS device. The piezoelectric component provides an inherent feedback signal and pre-charge source that enables electrostatic scavenging operation while the electrostatic device provides the proof mass that enables low frequency operation. The piezoelectric beam forms the spring of the resonant mass-spring transducer for converting vibration excitation into an AC electrical output. A serially poled, composite shim, piezoelectric bimorph produces the highest output rectified voltage of over 3.3V and power output of 145uW using ¼ g vibration acceleration at 120Hz. Considering solely the volume of the piezoelectric beam and tungsten proof mass, the volume is 0.054cm3, resulting in a power density of 2.68mW/cm3. Incorporation of a simple parallel plate structure that provides the proof mass for low frequency resonant operation in addition to cogeneration via electrostatic energy scavenging provides a 19.82 to 35.29 percent increase in voltage beyond the piezoelectric generated DC rails. This corresponds to approximately 2.1nW additional power from the electrostatic scavenger component and demonstrates the first instance of hybrid energy scavenging using both piezoelectric and synchronous electrostatic transduction. Furthermore, it provides a complete system architecture and development platform for additional enhancements that will enable in excess of 100uW additional power from the electrostatic scavenger

NASA Tech Briefs, September 2008

Topics covered include: Nanotip Carpets as Antireflection Surfaces; Nano-Engineered Catalysts for Direct Methanol Fuel Cells; Capillography of Mats of Nanofibers; Directed Growth of Carbon Nanotubes Across Gaps; High-Voltage, Asymmetric-Waveform Generator; Magic-T Junction Using Microstrip/Slotline Transitions; On-Wafer Measurement of a Silicon-Based CMOS VCO at 324 GHz; Group-III Nitride Field Emitters; HEMT Amplifiers and Equipment for their On-Wafer Testing; Thermal Spray Formation of Polymer Coatings; Improved Gas Filling and Sealing of an HC-PCF; Making More-Complex Molecules Using Superthermal Atom/Molecule Collisions; Nematic Cells for Digital Light Deflection; Improved Silica Aerogel Composite Materials; Microgravity, Mesh-Crawling Legged Robots; Advanced Active-Magnetic-Bearing Thrust- Measurement System; Thermally Actuated Hydraulic Pumps; A New, Highly Improved Two-Cycle Engine; Flexible Structural-Health-Monitoring Sheets; Alignment Pins for Assembling and Disassembling Structures; Purifying Nucleic Acids from Samples of Extremely Low Biomass; Adjustable-Viewing-Angle Endoscopic Tool for Skull Base and Brain Surgery; UV-Resistant Non-Spore-Forming Bacteria From Spacecraft-Assembly Facilities; Hard-X-Ray/Soft-Gamma-Ray Imaging Sensor Assembly for Astronomy; Simplified Modeling of Oxidation of Hydrocarbons; Near-Field Spectroscopy with Nanoparticles Deposited by AFM; Light Collimator and Monitor for a Spectroradiometer; Hyperspectral Fluorescence and Reflectance Imaging Instrument; Improving the Optical Quality Factor of the WGM Resonator; Ultra-Stable Beacon Source for Laboratory Testing of Optical Tracking; Transmissive Diffractive Optical Element Solar Concentrators; Delaying Trains of Short Light Pulses in WGM Resonators; Toward Better Modeling of Supercritical Turbulent Mixing; JPEG 2000 Encoding with Perceptual Distortion Control; Intelligent Integrated Health Management for a System of Systems; Delay Banking for Managing Air Traffic; and Spline-Based Smoothing of Airfoil Curvatures

In-Mold Assembly of Multi-Functional Structures

Combining the recent advances in injection moldable polymer composites with the multi-material molding techniques enable fabrication of multi-functional structures to serve multiple functions (e.g., carry load, support motion, dissipate heat, store energy). Current in-mold assembly methods, however, cannot be simply scaled to create structures with miniature features, as the process conditions and the assembly failure modes change with the feature size. This dissertation identifies and addresses the issues associated with the in-mold assembly of multi-functional structures with miniature components. First, the functional capability of embedding actuators is developed. As a part of this effort, computational modeling methods are developed to assess the functionality of the structure with respect to the material properties, process parameters and the heat source. Using these models, the effective material thermal conductivity required to dissipate the heat generated by the embedded small scale actuator is identified. Also, the influence of the fiber orientation on the heat dissipation performance is characterized. Finally, models for integrated product and process design are presented to ensure the miniature actuator survivability during embedding process. The second functional capability developed as a part of this dissertation is the in-mold assembly of multi-material structures capable of motion and load transfer, such as mechanisms with compliant hinges. The necessary hinge and link design features are identified. The shapes and orientations of these features are analyzed with respect to their functionality, mutual dependencies, and the process cost. The parametric model of the interface design is developed. This model is used to minimize both the final assembly weight and the mold complexity as the process cost measure. Also, to minimize the manufacturing waste and the risk of assembly failure due to unbalanced mold filling, the design optimization of runner systems used in multi-cavity molds for in-mold assembly is developed. The complete optimization model is characterized and formulated. The best method to solve the runner optimization problem is identified. To demonstrate the applicability of the tools developed in this dissertation towards the miniaturization of robotic devices, a case study of a novel miniature air vehicle drive mechanism is presented