ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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Channel hot carrier (CHC) is another dominant degradation mechanism which affects analog and mixed signal circuits (AMS) as transistor operates continuously in saturation condition. New model is proposed to account for e-e scattering in advanced technology nodes due to high gate electric field. The model is validated with 28nm and 65nm thick oxide data for different stress voltages. It demonstrates shift in worst case CHC condition to Vgs=Vds from Vgs=0.5Vds. A novel iteration based aging simulation framework for AMS designs is proposed which eliminates limitation for conventional reliability tools. This approach helps us identify a unique positive feedback mechanism termed as Bias Runaway. Bias runaway, is rapid increase of the bias voltage in AMS circuits which occurs when the feedback between the bias current and the effect of channel hot carrier turns into positive. The degradation of CHC is a gradual process but under specific circumstances, the degradation rate can be dramatically accelerated. Such a catastrophic phenomenon is highly sensitive to the initial operation condition, as well as transistor gate length. Based on 65nm silicon data, our work investigates the critical condition that triggers bias runaway, and the impact of gate length tuning. We develop new compact models as well as the simulation methodology for circuit diagnosis, and propose design solutions and the trade-offs to avoid bias runaway, which is vitally important to reliable AMS designs.
In this thesis, first the design of a highly reliable resistive random access memory (RRAM) PUF is presented. Compared to existing 1 cell/bit RRAM, here the sum of the read-out currents of multiple RRAM cells are used for generating one response bit. This method statistically minimizes any early-lifetime failure due to RRAM retention degradation at high temperature or under voltage stress. Using a device model that was calibrated using IMEC HfOx RRAM experimental data, it was shown that an 8 cells/bit architecture achieves 99.9999% reliability for a lifetime >10 years at 125℃ . Also, the hardware area overhead of the proposed 8 cells/bit RRAM PUF architecture was smaller than 1 cell/bit RRAM PUF that requires error correction coding to achieve the same reliability.
Next, a basic security primitive is presented, where the RRAM PUF is embedded in the cryptographic module, SHA-256. This architecture is referred to as Embedded PUF or EPUF. EPUF has a security advantage over SHA-256 as it never exposes the PUF response to the outside world. Instead, in each round, the PUF response is used to change a few bits of the message word to produce a unique message digest for each IC. The use of EPUF as a key generation module for AES is also shown. The hardware area requirement for SHA-256 and AES-128 is then analyzed using synthesis results based on TSMC 65nm library. It is shown that the area overhead of 8 cells/bit RRAM PUF is only 1.08% of the SHA-256 module and 0.04% of the AES-128 module. The security analysis of the PUF based systems is also presented. It is shown that the EPUF-based systems are resistant towards standard attacks on PUFs, and that the security of the cryptographic modules is not compromised.
This research project focuses on analyzing different growth techniques of thin films of Cobalt, Zirconium Tantalum Boron (CZTB) and the quality of the films resulted. The measurements include magnetic moment measurements using a Vibrating Sample Magnetometer, electrical measurements using 4 point resistivity methods and structural characterization using Scanning Electron Microscopy. Subtle changes in the growth mechanism result in different properties of these films and they are most suited for certain applications.
The growth methods presented in this research are oblique angled sputtering with localized magnetic field and oblique sputtering without presence of magnetic field. The uniaxial anisotropy can be controlled by changing the angle during sputtering. The resulting film of CZTB is tested for magnetic anisotropy and soft magnetism at room temperature by using Lakeshore 7500 Vibrating Sample Magnetometer. The results are presented, analyzed and explained using characterization techniques. Future work includes magnetic field presence during deposition, magnetic devices of this film with giga hertz range operating frequencies.
In the radiation environment, e.g. aerospace, the memory devices face different energetic particles. The strike of these energetic particles can generate electron-hole pairs (directly or indirectly) as they pass through the semiconductor device, resulting in photo-induced current, and may change the memory state. First, the trend of radiation effects of the mainstream memory technologies with technology node scaling is reviewed. Then, single event effects of the oxide based resistive switching random memory (RRAM), one of eNVM technologies, is investigated from the circuit-level to the system level.
Physical Unclonable Function (PUF) has been widely investigated as a promising hardware security primitive, which employs the inherent randomness in a physical system (e.g. the intrinsic semiconductor manufacturing variability). In the dissertation, two RRAM-based PUF implementations are proposed for cryptographic key generation (weak PUF) and device authentication (strong PUF), respectively. The performance of the RRAM PUFs are evaluated with experiment and simulation. The impact of non-ideal circuit effects on the performance of the PUFs is also investigated and optimization strategies are proposed to solve the non-ideal effects. Besides, the security resistance against modeling and machine learning attacks is analyzed as well.
Deep neural networks (DNNs) have shown remarkable improvements in various intelligent applications such as image classification, speech classification and object localization and detection. Increasing efforts have been devoted to develop hardware accelerators. In this dissertation, two types of compute-in-memory (CIM) based hardware accelerator designs with SRAM and eNVM technologies are proposed for two binary neural networks, i.e. hybrid BNN (HBNN) and XNOR-BNN, respectively, which are explored for the hardware resource-limited platforms, e.g. edge devices.. These designs feature with high the throughput, scalability, low latency and high energy efficiency. Finally, we have successfully taped-out and validated the proposed designs with SRAM technology in TSMC 65 nm.
Overall, this dissertation paves the paths for memory technologies’ new applications towards the secure and energy-efficient artificial intelligence system.
technology because of its attractive attributes, including excellent scalability (< 10 nm), low
programming voltage (< 3 V), fast switching speed (< 10 ns), high OFF/ON ratio (> 10),
good endurance (up to 1012 cycles) and great compatibility with silicon CMOS technology [1].
However, ReRAM suffers from larger write latency, energy and reliability issue compared to
Dynamic Random Access Memory (DRAM). To improve the energy-efficiency, latency efficiency and reliability of ReRAM storage systems, a low cost cross-layer approach that spans device, circuit, architecture and system levels is proposed.
For 1T1R 2D ReRAM system, the effect of both retention and endurance errors on
ReRAM reliability is considered. Proposed approach is to design circuit-level and architecture-level techniques to reduce raw Bit Error Rate significantly and then employ low cost Error Control Coding to achieve the desired lifetime.
For 1S1R 2D ReRAM system, a cross-point array with “multi-bit per access” per subarray
is designed for high energy-efficiency and good reliability. The errors due to cell-level as well
as array-level variations are analyzed and a low cost scheme to maintain reliability and latency
with low energy consumption is proposed.
For 1S1R 3D ReRAM system, access schemes which activate multiple subarrays with
multiple layers in a subarray are used to achieve high energy efficiency through activating fewer
subarray, and good reliability is achieved through innovative data organization.
Finally, a novel ReRAM-based accelerator design is proposed to support multiple
Convolutional Neural Networks (CNN) topologies including VGGNet, AlexNet and ResNet.
The multi-tiled architecture consists of 9 processing elements per tile, where each tile
implements the dot product operation using ReRAM as computation unit. The processing
elements operate in a systolic fashion, thereby maximizing input feature map reuse and
minimizing interconnection cost. The system-level evaluation on several network benchmarks
show that the proposed architecture can improve computation efficiency and energy efficiency
compared to a state-of-the-art ReRAM-based accelerator.
The research described in this dissertation consists of four main parts. First is a new circuit architecture of a differential threshold logic flipflop called PNAND. The PNAND gate is an edge-triggered multi-input sequential cell whose next state function is a threshold function of its inputs. Second a new approach, called hybridization, that replaces flipflops and parts of their logic cones with PNAND cells is described. The resulting \hybrid circuit, which consists of conventional logic cells and PNANDs, is shown to have significantly less power consumption, smaller area, less standby power and less power variation.
Third, a new architecture of a field programmable array, called field programmable threshold logic array (FPTLA), in which the standard lookup table (LUT) is replaced by a PNAND is described. The FPTLA is shown to have as much as 50% lower energy-delay product compared to conventional FPGA using well known FPGA modeling tool called VPR.
Fourth, a novel clock skewing technique that makes use of the completion detection feature of the differential mode flipflops is described. This clock skewing method improves the area and power of the ASIC circuits by increasing slack on timing paths. An additional advantage of this method is the elimination of hold time violation on given short paths.
Several circuit design methodologies such as retiming and asynchronous circuit design can use the proposed threshold logic gate effectively. Therefore, the use of threshold logic flipflops in conventional design methodologies opens new avenues of research towards more energy-efficient circuits.
In the second theme of this dissertation, a new model is presented to predict single event transients in 1T-1R memory arrays as an inverter, where the PMC is modeled as a constant resistance while the OFF transistor is model as a diode in parallel to a capacitance. The model divides the output voltage transient response of an inverter into three time segments, where an ionizing particle striking through the drain–body junction of the OFF-state NMOS is represented as a photocurrent pulse. If this current source is large enough, the output voltage can drop to a negative voltage. In this model, the OFF-state NMOS is represented as the parallel combination of an ideal diode and the intrinsic capacitance of the drain–body junction, while a resistance represents an ON-state NMOS. The proposed model is verified by 3-D TCAD mixed-mode device simulations. In order to investigate the flexibility of the model, the effects of important parameters, such as ON-state PMOS resistance, doping concentration of p-region in the diode, and the photocurrent pulse are scrutinized.
The third theme of this dissertation develops various models together with TCAD simulations to model the behavior of different diamond-based devices, including PIN diodes and bipolar junction transistors (BJTs). Diamond is a very attractive material for contemporary power semiconductor devices because of its excellent material properties, such as high breakdown voltage and superior thermal conductivity compared to other materials. Collectively, this research project enhances the development of high power and high temperature electronics using diamond-based semiconductors. During the fabrication process of diamond-based devices, structural defects particularly threading dislocations (TDs), may affect the device electrical properties, and models were developed to account of such defects. Recognition of their behavior helps us understand and predict the performance of diamond-based devices. Here, the electrical conductance through TD sites is shown to be governed by the Poole-Frenkel emission (PFE) for the temperature (T) range of 323 K ˂ T ˂ 423 K. Analytical models were performed to fit with experimental data over the aforementioned temperature range. Next, the Silvaco Atlas tool, a drift-diffusion based TCAD commercial software, was used to model diamond-based BJTs. Here, some field plate methods are proposed in order to decrease the surface electric field. The models used in Atlas are modified to account for both hopping transport in the impurity bands associated with high activation energies for boron doped and phosphorus doped diamond.