982 resultados para Hybrid integrated circuits
Resumo:
The study of ionizing radiation effects on semiconductor devices is of great relevance for the global technological development and is a necessity in some strategic areas in Brazil. This work presents preliminary results of radiation effects in MOSFETs that were exposed to 3.2 Grad radiation dose produced by a 2.6-MeV proton beam. The focus of this work was to electrically characterize a Rectangular-Gate MOSFET (RGT) and a Circular-Gate MOSFET (CGT), manufactured with the On Semiconductor 0.5 mu m standard CMOS fabrication process and to verify a suitable geometry for space applications. During the experiment, I-DS x V-GS curves were measured. After irradiation, the RGT off-state current (I-OFF) increased approximately two orders of magnitude reaching practically the same value of the I-OFF in the CGT, which only doubled its value. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
In this work we have studied the radiation effects on MOSFET electronic devices. The integrated circuits were exposed to 10 key X-ray radiation and 2.6 MeV energy proton beam. We have irradiated MOSFET devices with two different geometries: rectangular-gate transistor and circular-gate transistor. We have observed the cumulative dose provokes shifts on the threshold voltage and increases or decreases the transistor's off-state and leakage current. The position of the trapped charges in modern CMOS technology devices depends on radiation type, dose rate, total dose, applied bias and is a function of device geometry. We concluded the circular-gate transistor is more tolerant to radiation than the rectangular-gate transistor. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
Current SoC design trends are characterized by the integration of larger amount of IPs targeting a wide range of application fields. Such multi-application systems are constrained by a set of requirements. In such scenario network-on-chips (NoC) are becoming more important as the on-chip communication structure. Designing an optimal NoC for satisfying the requirements of each individual application requires the specification of a large set of configuration parameters leading to a wide solution space. It has been shown that IP mapping is one of the most critical parameters in NoC design, strongly influencing the SoC performance. IP mapping has been solved for single application systems using single and multi-objective optimization algorithms. In this paper we propose the use of a multi-objective adaptive immune algorithm (M(2)AIA), an evolutionary approach to solve the multi-application NoC mapping problem. Latency and power consumption were adopted as the target multi-objective functions. To compare the efficiency of our approach, our results are compared with those of the genetic and branch and bound multi-objective mapping algorithms. We tested 11 well-known benchmarks, including random and real applications, and combines up to 8 applications at the same SoC. The experimental results showed that the M(2)AIA decreases in average the power consumption and the latency 27.3 and 42.1 % compared to the branch and bound approach and 29.3 and 36.1 % over the genetic approach.
Resumo:
This paper presents a technique for performing analog design synthesis at circuit level providing feedback to the designer through the exploration of the Pareto frontier. A modified simulated annealing which is able to perform crossover with past anchor points when a local minimum is found which is used as the optimization algorithm on the initial synthesis procedure. After all specifications are met, the algorithm searches for the extreme points of the Pareto frontier in order to obtain a non-exhaustive exploration of the Pareto front. Finally, multi-objective particle swarm optimization is used to spread the results and to find a more accurate frontier. Piecewise linear functions are used as single-objective cost functions to produce a smooth and equal convergence of all measurements to the desired specifications during the composition of the aggregate objective function. To verify the presented technique two circuits were designed, which are: a Miller amplifier with 96 dB Voltage gain, 15.48 MHz unity gain frequency, slew rate of 19.2 V/mu s with a current supply of 385.15 mu A, and a complementary folded cascode with 104.25 dB Voltage gain, 18.15 MHz of unity gain frequency and a slew rate of 13.370 MV/mu s. These circuits were synthesized using a 0.35 mu m technology. The results show that the method provides a fast approach for good solutions using the modified SA and further good Pareto front exploration through its connection to the particle swarm optimization algorithm.
Resumo:
Field-Programmable Gate Arrays (FPGAs) are becoming increasingly important in embedded and high-performance computing systems. They allow performance levels close to the ones obtained with Application-Specific Integrated Circuits, while still keeping design and implementation flexibility. However, to efficiently program FPGAs, one needs the expertise of hardware developers in order to master hardware description languages (HDLs) such as VHDL or Verilog. Attempts to furnish a high-level compilation flow (e.g., from C programs) still have to address open issues before broader efficient results can be obtained. Bearing in mind an FPGA available resources, it has been developed LALP (Language for Aggressive Loop Pipelining), a novel language to program FPGA-based accelerators, and its compilation framework, including mapping capabilities. The main ideas behind LALP are to provide a higher abstraction level than HDLs, to exploit the intrinsic parallelism of hardware resources, and to allow the programmer to control execution stages whenever the compiler techniques are unable to generate efficient implementations. Those features are particularly useful to implement loop pipelining, a well regarded technique used to accelerate computations in several application domains. This paper describes LALP, and shows how it can be used to achieve high-performance computing solutions.
Resumo:
Graphene has received great attention due to its exceptional properties, which include corners with zero effective mass, extremely large mobilities, this could render it the new template for the next generation of electronic devices. Furthermore it has weak spin orbit interaction because of the low atomic number of carbon atom in turn results in long spin coherence lengths. Therefore, graphene is also a promising material for future applications in spintronic devices - the use of electronic spin degrees of freedom instead of the electron charge. Graphene can be engineered to form a number of different structures. In particular, by appropriately cutting it one can obtain 1-D system -with only a few nanometers in width - known as graphene nanoribbon, which strongly owe their properties to the width of the ribbons and to the atomic structure along the edges. Those GNR-based systems have been shown to have great potential applications specially as connectors for integrated circuits. Impurities and defects might play an important role to the coherence of these systems. In particular, the presence of transition metal atoms can lead to significant spin-flip processes of conduction electrons. Understanding this effect is of utmost importance for spintronics applied design. In this work, we focus on electronic transport properties of armchair graphene nanoribbons with adsorbed transition metal atoms as impurities and taking into account the spin-orbit effect. Our calculations were performed using a combination of density functional theory and non-equilibrium Greens functions. Also, employing a recursive method we consider a large number of impurities randomly distributed along the nanoribbon in order to infer, for different concentrations of defects, the spin-coherence length.
Resumo:
Technology scaling increasingly emphasizes complexity and non-ideality of the electrical behavior of semiconductor devices and boosts interest on alternatives to the conventional planar MOSFET architecture. TCAD simulation tools are fundamental to the analysis and development of new technology generations. However, the increasing device complexity is reflected in an augmented dimensionality of the problems to be solved. The trade-off between accuracy and computational cost of the simulation is especially influenced by domain discretization: mesh generation is therefore one of the most critical steps and automatic approaches are sought. Moreover, the problem size is further increased by process variations, calling for a statistical representation of the single device through an ensemble of microscopically different instances. The aim of this thesis is to present multi-disciplinary approaches to handle this increasing problem dimensionality in a numerical simulation perspective. The topic of mesh generation is tackled by presenting a new Wavelet-based Adaptive Method (WAM) for the automatic refinement of 2D and 3D domain discretizations. Multiresolution techniques and efficient signal processing algorithms are exploited to increase grid resolution in the domain regions where relevant physical phenomena take place. Moreover, the grid is dynamically adapted to follow solution changes produced by bias variations and quality criteria are imposed on the produced meshes. The further dimensionality increase due to variability in extremely scaled devices is considered with reference to two increasingly critical phenomena, namely line-edge roughness (LER) and random dopant fluctuations (RD). The impact of such phenomena on FinFET devices, which represent a promising alternative to planar CMOS technology, is estimated through 2D and 3D TCAD simulations and statistical tools, taking into account matching performance of single devices as well as basic circuit blocks such as SRAMs. Several process options are compared, including resist- and spacer-defined fin patterning as well as different doping profile definitions. Combining statistical simulations with experimental data, potentialities and shortcomings of the FinFET architecture are analyzed and useful design guidelines are provided, which boost feasibility of this technology for mainstream applications in sub-45 nm generation integrated circuits.
Resumo:
For many years, RF and analog integrated circuits have been mainly developed using bipolar and compound semiconductor technologies due to their better performance. In the last years, the advance made in CMOS technology allowed analog and RF circuits to be built with such a technology, but the use of CMOS technology in RF application instead of bipolar technology has brought more issues in terms of noise. The noise cannot be completely eliminated and will therefore ultimately limit the accuracy of measurements and set a lower limit on how small signals can be detected and processed in an electronic circuit. One kind of noise which affects MOS transistors much more than bipolar ones is the low-frequency noise. In MOSFETs, low-frequency noise is mainly of two kinds: flicker or 1/f noise and random telegraph signal noise (RTS). The objective of this thesis is to characterize and to model the low-frequency noise by studying RTS and flicker noise under both constant and switched bias conditions. The effect of different biasing schemes on both RTS and flicker noise in time and frequency domain has been investigated.
Resumo:
The digital electronic market development is founded on the continuous reduction of the transistors size, to reduce area, power, cost and increase the computational performance of integrated circuits. This trend, known as technology scaling, is approaching the nanometer size. The lithographic process in the manufacturing stage is increasing its uncertainty with the scaling down of the transistors size, resulting in a larger parameter variation in future technology generations. Furthermore, the exponential relationship between the leakage current and the threshold voltage, is limiting the threshold and supply voltages scaling, increasing the power density and creating local thermal issues, such as hot spots, thermal runaway and thermal cycles. In addiction, the introduction of new materials and the smaller devices dimension are reducing transistors robustness, that combined with high temperature and frequently thermal cycles, are speeding up wear out processes. Those effects are no longer addressable only at the process level. Consequently the deep sub-micron devices will require solutions which will imply several design levels, as system and logic, and new approaches called Design For Manufacturability (DFM) and Design For Reliability. The purpose of the above approaches is to bring in the early design stages the awareness of the device reliability and manufacturability, in order to introduce logic and system able to cope with the yield and reliability loss. The ITRS roadmap suggests the following research steps to integrate the design for manufacturability and reliability in the standard CAD automated design flow: i) The implementation of new analysis algorithms able to predict the system thermal behavior with the impact to the power and speed performances. ii) High level wear out models able to predict the mean time to failure of the system (MTTF). iii) Statistical performance analysis able to predict the impact of the process variation, both random and systematic. The new analysis tools have to be developed beside new logic and system strategies to cope with the future challenges, as for instance: i) Thermal management strategy that increase the reliability and life time of the devices acting to some tunable parameter,such as supply voltage or body bias. ii) Error detection logic able to interact with compensation techniques as Adaptive Supply Voltage ASV, Adaptive Body Bias ABB and error recovering, in order to increase yield and reliability. iii) architectures that are fundamentally resistant to variability, including locally asynchronous designs, redundancy, and error correcting signal encodings (ECC). The literature already features works addressing the prediction of the MTTF, papers focusing on thermal management in the general purpose chip, and publications on statistical performance analysis. In my Phd research activity, I investigated the need for thermal management in future embedded low-power Network On Chip (NoC) devices.I developed a thermal analysis library, that has been integrated in a NoC cycle accurate simulator and in a FPGA based NoC simulator. The results have shown that an accurate layout distribution can avoid the onset of hot-spot in a NoC chip. Furthermore the application of thermal management can reduce temperature and number of thermal cycles, increasing the systemreliability. Therefore the thesis advocates the need to integrate a thermal analysis in the first design stages for embedded NoC design. Later on, I focused my research in the development of statistical process variation analysis tool that is able to address both random and systematic variations. The tool was used to analyze the impact of self-timed asynchronous logic stages in an embedded microprocessor. As results we confirmed the capability of self-timed logic to increase the manufacturability and reliability. Furthermore we used the tool to investigate the suitability of low-swing techniques in the NoC system communication under process variations. In this case We discovered the superior robustness to systematic process variation of low-swing links, which shows a good response to compensation technique as ASV and ABB. Hence low-swing is a good alternative to the standard CMOS communication for power, speed, reliability and manufacturability. In summary my work proves the advantage of integrating a statistical process variation analysis tool in the first stages of the design flow.
Resumo:
The work of the present thesis is focused on the implementation of microelectronic voltage sensing devices, with the purpose of transmitting and extracting analog information between devices of different nature at short distances or upon contact. Initally, chip-to-chip communication has been studied, and circuitry for 3D capacitive coupling has been implemented. Such circuits allow the communication between dies fabricated in different technologies. Due to their novelty, they are not standardized and currently not supported by standard CAD tools. In order to overcome such burden, a novel approach for the characterization of such communicating links has been proposed. This results in shorter design times and increased accuracy. Communication between an integrated circuit (IC) and a probe card has been extensively studied as well. Today wafer probing is a costly test procedure with many drawbacks, which could be overcome by a different communication approach such as capacitive coupling. For this reason wireless wafer probing has been investigated as an alternative approach to standard on-contact wafer probing. Interfaces between integrated circuits and biological systems have also been investigated. Active electrodes for simultaneous electroencephalography (EEG) and electrical impedance tomography (EIT) have been implemented for the first time in a 0.35 um process. Number of wires has been minimized by sharing the analog outputs and supply on a single wire, thus implementing electrodes that require only 4 wires for their operation. Minimization of wires reduces the cable weight and thus limits the patient's discomfort. The physical channel for communication between an IC and a biological medium is represented by the electrode itself. As this is a very crucial point for biopotential acquisitions, large efforts have been carried in order to investigate the different electrode technologies and geometries and an electromagnetic model is presented in order to characterize the properties of the electrode to skin interface.
Resumo:
The improvement of devices provided by Nanotechnology has put forward new classes of sensors, called bio-nanosensors, which are very promising for the detection of biochemical molecules in a large variety of applications. Their use in lab-on-a-chip could gives rise to new opportunities in many fields, from health-care and bio-warfare to environmental and high-throughput screening for pharmaceutical industry. Bio-nanosensors have great advantages in terms of cost, performance, and parallelization. Indeed, they require very low quantities of reagents and improve the overall signal-to-noise-ratio due to increase of binding signal variations vs. area and reduction of stray capacitances. Additionally, they give rise to new challenges, such as the need to design high-performance low-noise integrated electronic interfaces. This thesis is related to the design of high-performance advanced CMOS interfaces for electrochemical bio-nanosensors. The main focus of the thesis is: 1) critical analysis of noise in sensing interfaces, 2) devising new techniques for noise reduction in discrete-time approaches, 3) developing new architectures for low-noise, low-power sensing interfaces. The manuscript reports a multi-project activity focusing on low-noise design and presents two developed integrated circuits (ICs) as examples of advanced CMOS interfaces for bio-nanosensors. The first project concerns low-noise current-sensing interface for DC and transient measurements of electrophysiological signals. The focus of this research activity is on the noise optimization of the electronic interface. A new noise reduction technique has been developed so as to realize an integrated CMOS interfaces with performance comparable with state-of-the-art instrumentations. The second project intends to realize a stand-alone, high-accuracy electrochemical impedance spectroscopy interface. The system is tailored for conductivity-temperature-depth sensors in environmental applications, as well as for bio-nanosensors. It is based on a band-pass delta-sigma technique and combines low-noise performance with low-power requirements.
Resumo:
In this report a new automated optical test for next generation of photonic integrated circuits (PICs) is provided by the test-bed design and assessment. After a briefly analysis of critical problems of actual optical tests, the main test features are defined: automation and flexibility, relaxed alignment procedure, speed up of entire test and data reliability. After studying varied solutions, the test-bed components are defined to be lens array, photo-detector array, and software controller. Each device is studied and calibrated, the spatial resolution, and reliability against interference at the photo-detector array are studied. The software is programmed in order to manage both PIC input, and photo-detector array output as well as data analysis. The test is validated by analysing state-of-art 16 ports PIC: the waveguide location, current versus power, and time-spatial power distribution are measured as well as the optical continuity of an entire path of PIC. Complexity, alignment tolerance, time of measurement are also discussed.
Resumo:
Thermal effects are rapidly gaining importance in nanometer heterogeneous integrated systems. Increased power density, coupled with spatio-temporal variability of chip workload, cause lateral and vertical temperature non-uniformities (variations) in the chip structure. The assumption of an uniform temperature for a large circuit leads to inaccurate determination of key design parameters. To improve design quality, we need precise estimation of temperature at detailed spatial resolution which is very computationally intensive. Consequently, thermal analysis of the designs needs to be done at multiple levels of granularity. To further investigate the flow of chip/package thermal analysis we exploit the Intel Single Chip Cloud Computer (SCC) and propose a methodology for calibration of SCC on-die temperature sensors. We also develop an infrastructure for online monitoring of SCC temperature sensor readings and SCC power consumption. Having the thermal simulation tool in hand, we propose MiMAPT, an approach for analyzing delay, power and temperature in digital integrated circuits. MiMAPT integrates seamlessly into industrial Front-end and Back-end chip design flows. It accounts for temperature non-uniformities and self-heating while performing analysis. Furthermore, we extend the temperature variation aware analysis of designs to 3D MPSoCs with Wide-I/O DRAM. We improve the DRAM refresh power by considering the lateral and vertical temperature variations in the 3D structure and adapting the per-DRAM-bank refresh period accordingly. We develop an advanced virtual platform which models the performance, power, and thermal behavior of a 3D-integrated MPSoC with Wide-I/O DRAMs in detail. Moving towards real-world multi-core heterogeneous SoC designs, a reconfigurable heterogeneous platform (ZYNQ) is exploited to further study the performance and energy efficiency of various CPU-accelerator data sharing methods in heterogeneous hardware architectures. A complete hardware accelerator featuring clusters of OpenRISC CPUs, with dynamic address remapping capability is built and verified on a real hardware.
Resumo:
Organic semiconductors with the unique combination of electronic and mechanical properties may offer cost-effective ways of realizing many electronic applications, e.g. large-area flexible displays, printed integrated circuits and plastic solar cells. In order to facilitate the rational compound design of organic semiconductors, it is essential to understand relevant physical properties e.g. charge transport. This, however, is not straightforward, since physical models operating on different time and length scales need to be combined. First, the material morphology has to be known at an atomistic scale. For this atomistic molecular dynamics simulations can be employed, provided that an atomistic force field is available. Otherwise it has to be developed based on the existing force fields and first principle calculations. However, atomistic simulations are typically limited to the nanometer length- and nanosecond time-scales. To overcome these limitations, systematic coarse-graining techniques can be used. In the first part of this thesis, it is demonstrated how a force field can be parameterized for a typical organic molecule. Then different coarse-graining approaches are introduced together with the analysis of their advantages and problems. When atomistic morphology is available, charge transport can be studied by combining the high-temperature Marcus theory with kinetic Monte Carlo simulations. The approach is applied to the hole transport in amorphous films of tris(8-hydroxyquinoline)aluminium (Alq3). First the influence of the force field parameters and the corresponding morphological changes on charge transport is studied. It is shown that the energetic disorder plays an important role for amorphous Alq3, defining charge carrier dynamics. Its spatial correlations govern the Poole-Frenkel behavior of the charge carrier mobility. It is found that hole transport is dispersive for system sizes accessible to simulations, meaning that calculated mobilities depend strongly on the system size. A method for extrapolating calculated mobilities to the infinite system size is proposed, allowing direct comparison of simulation results and time-of-flight experiments. The extracted value of the nondispersive hole mobility and its electric field dependence for amorphous Alq3 agree well with the experimental results.
Resumo:
For half a century the integrated circuits (ICs) that make up the heart of electronic devices have been steadily improving by shrinking at an exponential rate. However, as the current crop of ICs get smaller and the insulating layers involved become thinner, electrons leak through due to quantum mechanical tunneling. This is one of several issues which will bring an end to this incredible streak of exponential improvement of this type of transistor device, after which future improvements will have to come from employing fundamentally different transistor architecture rather than fine tuning and miniaturizing the metal-oxide-semiconductor field effect transistors (MOSFETs) in use today. Several new transistor designs, some designed and built here at Michigan Tech, involve electrons tunneling their way through arrays of nanoparticles. We use a multi-scale approach to model these devices and study their behavior. For investigating the tunneling characteristics of the individual junctions, we use a first-principles approach to model conduction between sub-nanometer gold particles. To estimate the change in energy due to the movement of individual electrons, we use the finite element method to calculate electrostatic capacitances. The kinetic Monte Carlo method allows us to use our knowledge of these details to simulate the dynamics of an entire device— sometimes consisting of hundreds of individual particles—and watch as a device ‘turns on’ and starts conducting an electric current. Scanning tunneling microscopy (STM) and the closely related scanning tunneling spectroscopy (STS) are a family of powerful experimental techniques that allow for the probing and imaging of surfaces and molecules at atomic resolution. However, interpretation of the results often requires comparison with theoretical and computational models. We have developed a new method for calculating STM topographs and STS spectra. This method combines an established method for approximating the geometric variation of the electronic density of states, with a modern method for calculating spin-dependent tunneling currents, offering a unique balance between accuracy and accessibility.