Matching Items (43)
Description
A fully automated logic design methodology for radiation hardened by design (RHBD) high speed logic using fine grained triple modular redundancy (TMR) is presented. The hardening techniques used in the cell library are described and evaluated, with a focus on both layout techniques that mitigate total ionizing dose (TID) and latchup issues and flip-flop designs that mitigate single event transient (SET) and single event upset (SEU) issues. The base TMR self-correcting master-slave flip-flop is described and compared to more traditional hardening techniques. Additional refinements are presented, including testability features that disable the self-correction to allow detection of manufacturing defects. The circuit approach is validated for hardness using both heavy ion and proton broad beam testing. For synthesis and auto place and route, the methodology and circuits leverage commercial logic design automation tools. These tools are glued together with custom CAD tools designed to enable easy conversion of standard single redundant hardware description language (HDL) files into hardened TMR circuitry. The flow allows hardening of any synthesizable logic at clock frequencies comparable to unhardened designs and supports standard low-power techniques, e.g. clock gating and supply voltage scaling.
ContributorsHindman, Nathan (Author) / Clark, Lawrence T (Thesis advisor) / Holbert, Keith E. (Committee member) / Barnaby, Hugh (Committee member) / Allee, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
Microprocessors are the processing heart of any digital system and are central to all the technological advancements of the age including space exploration and monitoring. The demands of space exploration require a special class of microprocessors called radiation hardened microprocessors which are less susceptible to radiation present outside the earth's atmosphere, in other words their functioning is not disrupted even in presence of disruptive radiation. The presence of these particles forces the designers to come up with design techniques at circuit and chip levels to alleviate the errors which can be encountered in the functioning of microprocessors. Microprocessor evolution has been very rapid in terms of performance but the same cannot be said about its rad-hard counterpart. With the total data processing capability overall increasing rapidly, the clear lack of performance of the processors manifests as a bottleneck in any processing system. To design high performance rad-hard microprocessors designers have to overcome difficult design problems at various design stages i.e. Architecture, Synthesis, Floorplanning, Optimization, routing and analysis all the while maintaining circuit radiation hardness. The reference design `HERMES' is targeted at 90nm IBM G process and is expected to reach 500Mhz which is twice as fast any processor currently available. Chapter 1 talks about the mechanisms of radiation effects which cause upsets and degradation to the functioning of digital circuits. Chapter 2 gives a brief description of the components which are used in the design and are part of the consistent efforts at ASUVLSI lab culminating in this chip level implementation of the design. Chapter 3 explains the basic digital design ASIC flow and the changes made to it leading to a rad-hard specific ASIC flow used in implementing this chip. Chapter 4 talks about the triple mode redundant (TMR) specific flow which is used in the block implementation, delineating the challenges faced and the solutions proposed to make the flow work. Chapter 5 explains the challenges faced and solutions arrived at while using the top-level flow described in chapter 3. Chapter 6 puts together the results and analyzes the design in terms of basic integrated circuit design constraints.
ContributorsRamamurthy, Chandarasekaran (Author) / Clark, Lawrence T (Thesis advisor) / Holbert, Keith E. (Committee member) / Barnaby, Hugh J (Committee member) / Mayhew, David (Committee member) / Arizona State University (Publisher)
Created2013
Description
Thin film transistors (TFTs) are being used in a wide variety of applications such as image sensors, radiation detectors, as well as for use in liquid crystal displays. However, there is a conspicuous absence of interface electronics for bridging the gap between the flexible sensors and digitized displays. Hence is the need to build the same. In this thesis, the feasibility of building mixed analog circuits in TFTs are explored and demonstrated. A flexible CMOS op-amp is demonstrated using a-Si:H and pentacene TFTs. The achieved performance is ¡Ö 50 dB of DC open loop gain with unity gain frequency (UGF) of 7 kHz. The op-amp is built on the popular 2 stage topology with the 2nd stage being cascoded to provide sufficient gain. A novel biasing circuit was successfully developed modifying the gm biasing circuit to retard the performance degradation as the TFTs aged. A switched capacitor 7 bit DAC was developed in only nMOS topology using a-Si:H TFTs, based on charge sharing concept. The DAC achieved a maximum differential non-linearity (DNL) of 0.6 least significant bit (LSB), while the maximum integral non-linearity (INL) was 1 LSB. TFTs were used as switches in this architecture; as a result the performance was quite unchanged even as the TFTs degraded. A 5 bit fully flash ADC was also designed using all nMOS a-Si:H TFTs. Gray coding was implemented at the output to avoid errors due to comparator meta-stability. Finally a 5 bit current steering DAC was also built using all nMOS a-Si:H TFTs. However, due to process variation, the DNL was increased to 1.2 while the INL was about 1.8 LSB. Measurements were made on the external stress effects on zinc indium oxide (ZIO) TFTs. Electrically induced stresses were studied applying DC bias on the gate and drain. These stresses shifted the device characteristics like threshold voltage and mobility. The TFTs were then mechanically stressed by stretching them across cylindrical structures of various radii. Both the subthreshold swing and mobility underwent significant changes when the stress was tensile while the change was minor under compressive stress, applied parallel to channel length.
ContributorsDey, Aritra (Author) / Allee, David R. (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Garrity, Douglas A (Committee member) / Song, Hongjiang (Committee member) / Clark, Lawrence T (Committee member) / Arizona State University (Publisher)
Created2011
Description
The geometric growth in the integrated circuit technology due to transistor scaling also with system-on-chip design strategy, the complexity of the integrated circuit has increased manifold. Short time to market with high reliability and performance is one of the most competitive challenges. Both custom and ASIC design methodologies have evolved over the time to cope with this but the high manual labor in custom and statistic design in ASIC are still causes of concern. This work proposes a new circuit design strategy that focuses mostly on arrayed structures like TLB, RF, Cache, IPCAM etc. that reduces the manual effort to a great extent and also makes the design regular, repetitive still achieving high performance. The method proposes making the complete design custom schematic but using the standard cells. This requires adding some custom cells to the already exhaustive library to optimize the design for performance. Once schematic is finalized, the designer places these standard cells in a spreadsheet, placing closely the cells in the critical paths. A Perl script then generates Cadence Encounter compatible placement file. The design is then routed in Encounter. Since designer is the best judge of the circuit architecture, placement by the designer will allow achieve most optimal design. Several designs like IPCAM, issue logic, TLB, RF and Cache designs were carried out and the performance were compared against the fully custom and ASIC flow. The TLB, RF and Cache were the part of the HEMES microprocessor.
ContributorsMaurya, Satendra Kumar (Author) / Clark, Lawrence T (Thesis advisor) / Holbert, Keith E. (Committee member) / Vrudhula, Sarma (Committee member) / Allee, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
Circuits on smaller technology nodes become more vulnerable to radiation-induced upset. Since this is a major problem for electronic circuits used in space applications, designers have a variety of solutions in hand. Radiation hardening by design (RHBD) is an approach, where electronic components are designed to work properly in certain radiation environments without the use of special fabrication processes. This work focuses on the cache design for a high performance microprocessor. The design tries to mitigate radiation effects like SEE, on a commercial foundry 45 nm SOI process. The design has been ported from a previously done cache design at the 90 nm process node. The cache design is a 16 KB, 4 way set associative, write-through design that uses a no-write allocate policy. The cache has been tested to write and read at above 2 GHz at VDD = 0.9 V. Interleaved layout, parity protection, dual redundancy, and checking circuits are used in the design to achieve radiation hardness. High speed is accomplished through the use of dynamic circuits and short wiring routes wherever possible. Gated clocks and optimized wire connections are used to reduce power. Structured methodology is used to build up the entire cache.
ContributorsXavier, Jerin (Author) / Clark, Lawrence T (Thesis advisor) / Cao, Yu (Committee member) / Allee, David R. (Committee member) / Arizona State University (Publisher)
Created2012
Description
Clock generation and distribution are essential to CMOS microchips, providing synchronization to external devices and between internal sequential logic. Clocks in microprocessors are highly vulnerable to single event effects and designing reliable energy efficient clock networks for mission critical applications is a major challenge. This dissertation studies the basics of radiation hardening, essentials of clock design and impact of particle strikes on clocks in detail and presents design techniques for hardening complete clock systems in digital ICs.
Since the sequential elements play a key role in deciding the robustness of any clocking strategy, hardened-by-design implementations of triple-mode redundant (TMR) pulse clocked latches and physical design methodologies for using TMR master-slave flip-flops in application specific ICs (ASICs) are proposed. A novel temporal pulse clocked latch design for low power radiation hardened applications is also proposed. Techniques for designing custom RHBD clock distribution networks (clock spines) and ASIC clock trees for a radiation hardened microprocessor using standard CAD tools are presented. A framework for analyzing the vulnerabilities of clock trees in general, and study the parameters that contribute the most to the tree’s failure, including impact on controlled latches is provided. This is then used to design an integrated temporally redundant clock tree and pulse clocked flip-flop based clocking scheme that is robust to single event transients (SETs) and single event upsets (SEUs). Subsequently, designing robust clock delay lines for use in double data rate (DDRx) memory applications is studied in detail. Several modules of the proposed radiation hardened all-digital delay locked loop are designed and studied. Many of the circuits proposed in this entire body of work have been implemented and tested on a standard low-power 90-nm process.
Since the sequential elements play a key role in deciding the robustness of any clocking strategy, hardened-by-design implementations of triple-mode redundant (TMR) pulse clocked latches and physical design methodologies for using TMR master-slave flip-flops in application specific ICs (ASICs) are proposed. A novel temporal pulse clocked latch design for low power radiation hardened applications is also proposed. Techniques for designing custom RHBD clock distribution networks (clock spines) and ASIC clock trees for a radiation hardened microprocessor using standard CAD tools are presented. A framework for analyzing the vulnerabilities of clock trees in general, and study the parameters that contribute the most to the tree’s failure, including impact on controlled latches is provided. This is then used to design an integrated temporally redundant clock tree and pulse clocked flip-flop based clocking scheme that is robust to single event transients (SETs) and single event upsets (SEUs). Subsequently, designing robust clock delay lines for use in double data rate (DDRx) memory applications is studied in detail. Several modules of the proposed radiation hardened all-digital delay locked loop are designed and studied. Many of the circuits proposed in this entire body of work have been implemented and tested on a standard low-power 90-nm process.
ContributorsChellappa, Srivatsan (Author) / Clark, Lawrence T (Thesis advisor) / Holbert, Keith E. (Committee member) / Cao, Yu (Committee member) / Ogras, Umit Y. (Committee member) / Arizona State University (Publisher)
Created2015
Description
Caches have long been used to reduce memory access latency. However, the increased complexity of cache coherence brings significant challenges in processor design as the number of cores increases. While making caches scalable is still an important research problem, some researchers are exploring the possibility of a more power-efficient SRAM called scratchpad memories or SPMs. SPMs consume significantly less area, and are more energy-efficient per access than caches, and therefore make the design of on-chip memories much simpler. Unlike caches, which fetch data from memories automatically, an SPM requires explicit instructions for data transfers. SPM-only architectures are thus named as software managed manycore (SMM), since the data movements of such architectures rely on software. SMM processors have been widely used in different areas, such as embedded computing, network processing, or even high performance computing. While SMM processors provide a low-power platform, the hardware alone does not guarantee power efficiency, if applications on such processors deliver low performance. Efficient software techniques are therefore required. A big body of management techniques for SMM architectures are compiler-directed, as inserting data movement operations by hand forces programmers to trace flow of data, which can be error-prone and sometimes difficult if not impossible. This thesis develops compiler-directed techniques to manage data transfers for embedded applications on SMMs efficiently. The techniques analyze and find out the proper program points and insert data movement instructions accordingly. The techniques manage code, stack and heap data of applications, and reduce execution time by 14%, 52% and 80% respectively compared to their predecessors on typical embedded applications. On top of managing local data, a technique is also developed for shared data in SMM architectures. Experimental results show it achieves more than 2X speedup than the previous technique on average.
ContributorsCai, Jian (Author) / Shrivastava, Aviral (Thesis advisor) / Wu, Carole (Committee member) / Ren, Fengbo (Committee member) / Dasgupta, Partha (Committee member) / Arizona State University (Publisher)
Created2017
Description
With the end of Dennard scaling and Moore's law, architects have moved towards
heterogeneous designs consisting of specialized cores to achieve higher performance
and energy efficiency for a target application domain. Applications of linear algebra
are ubiquitous in the field of scientific computing, machine learning, statistics,
etc. with matrix computations being fundamental to these linear algebra based solutions.
Design of multiple dense (or sparse) matrix computation routines on the
same platform is quite challenging. Added to the complexity is the fact that dense
and sparse matrix computations have large differences in their storage and access
patterns and are difficult to optimize on the same architecture. This thesis addresses
this challenge and introduces a reconfigurable accelerator that supports both dense
and sparse matrix computations efficiently.
The reconfigurable architecture has been optimized to execute the following linear
algebra routines: GEMV (Dense General Matrix Vector Multiplication), GEMM
(Dense General Matrix Matrix Multiplication), TRSM (Triangular Matrix Solver),
LU Decomposition, Matrix Inverse, SpMV (Sparse Matrix Vector Multiplication),
SpMM (Sparse Matrix Matrix Multiplication). It is a multicore architecture where
each core consists of a 2D array of processing elements (PE).
The 2D array of PEs is of size 4x4 and is scheduled to perform 4x4 sized matrix
updates efficiently. A sequence of such updates is used to solve a larger problem inside
a core. A novel partitioned block compressed sparse data structure (PBCSC/PBCSR)
is used to perform sparse kernel updates. Scalable partitioning and mapping schemes
are presented that map input matrices of any given size to the multicore architecture.
Design trade-offs related to the PE array dimension, size of local memory inside a core
and the bandwidth between on-chip memories and the cores have been presented. An
optimal core configuration is developed from this analysis. Synthesis results using a 7nm PDK show that the proposed accelerator can achieve a performance of upto
32 GOPS using a single core.
heterogeneous designs consisting of specialized cores to achieve higher performance
and energy efficiency for a target application domain. Applications of linear algebra
are ubiquitous in the field of scientific computing, machine learning, statistics,
etc. with matrix computations being fundamental to these linear algebra based solutions.
Design of multiple dense (or sparse) matrix computation routines on the
same platform is quite challenging. Added to the complexity is the fact that dense
and sparse matrix computations have large differences in their storage and access
patterns and are difficult to optimize on the same architecture. This thesis addresses
this challenge and introduces a reconfigurable accelerator that supports both dense
and sparse matrix computations efficiently.
The reconfigurable architecture has been optimized to execute the following linear
algebra routines: GEMV (Dense General Matrix Vector Multiplication), GEMM
(Dense General Matrix Matrix Multiplication), TRSM (Triangular Matrix Solver),
LU Decomposition, Matrix Inverse, SpMV (Sparse Matrix Vector Multiplication),
SpMM (Sparse Matrix Matrix Multiplication). It is a multicore architecture where
each core consists of a 2D array of processing elements (PE).
The 2D array of PEs is of size 4x4 and is scheduled to perform 4x4 sized matrix
updates efficiently. A sequence of such updates is used to solve a larger problem inside
a core. A novel partitioned block compressed sparse data structure (PBCSC/PBCSR)
is used to perform sparse kernel updates. Scalable partitioning and mapping schemes
are presented that map input matrices of any given size to the multicore architecture.
Design trade-offs related to the PE array dimension, size of local memory inside a core
and the bandwidth between on-chip memories and the cores have been presented. An
optimal core configuration is developed from this analysis. Synthesis results using a 7nm PDK show that the proposed accelerator can achieve a performance of upto
32 GOPS using a single core.
ContributorsAnimesh, Saurabh (Author) / Chakrabarti, Chaitali (Thesis advisor) / Brunhaver, John (Committee member) / Ren, Fengbo (Committee member) / Arizona State University (Publisher)
Created2018
Description
Information forensics and security have come a long way in just a few years thanks to the recent advances in biometric recognition. The main challenge remains a proper design of a biometric modality that can be resilient to unconstrained conditions, such as quality distortions. This work presents a solution to face and ear recognition under unconstrained visual variations, with a main focus on recognition in the presence of blur, occlusion and additive noise distortions.
First, the dissertation addresses the problem of scene variations in the presence of blur, occlusion and additive noise distortions resulting from capture, processing and transmission. Despite their excellent performance, ’deep’ methods are susceptible to visual distortions, which significantly reduce their performance. Sparse representations, on the other hand, have shown huge potential capabilities in handling problems, such as occlusion and corruption. In this work, an augmented SRC (ASRC) framework is presented to improve the performance of the Spare Representation Classifier (SRC) in the presence of blur, additive noise and block occlusion, while preserving its robustness to scene dependent variations. Different feature types are considered in the performance evaluation including image raw pixels, HoG and deep learning VGG-Face. The proposed ASRC framework is shown to outperform the conventional SRC in terms of recognition accuracy, in addition to other existing sparse-based methods and blur invariant methods at medium to high levels of distortion, when particularly used with discriminative features.
In order to assess the quality of features in improving both the sparsity of the representation and the classification accuracy, a feature sparse coding and classification index (FSCCI) is proposed and used for feature ranking and selection within both the SRC and ASRC frameworks.
The second part of the dissertation presents a method for unconstrained ear recognition using deep learning features. The unconstrained ear recognition is performed using transfer learning with deep neural networks (DNNs) as a feature extractor followed by a shallow classifier. Data augmentation is used to improve the recognition performance by augmenting the training dataset with image transformations. The recognition performance of the feature extraction models is compared with an ensemble of fine-tuned networks. The results show that, in the case where long training time is not desirable or a large amount of data is not available, the features from pre-trained DNNs can be used with a shallow classifier to give a comparable recognition accuracy to the fine-tuned networks.
First, the dissertation addresses the problem of scene variations in the presence of blur, occlusion and additive noise distortions resulting from capture, processing and transmission. Despite their excellent performance, ’deep’ methods are susceptible to visual distortions, which significantly reduce their performance. Sparse representations, on the other hand, have shown huge potential capabilities in handling problems, such as occlusion and corruption. In this work, an augmented SRC (ASRC) framework is presented to improve the performance of the Spare Representation Classifier (SRC) in the presence of blur, additive noise and block occlusion, while preserving its robustness to scene dependent variations. Different feature types are considered in the performance evaluation including image raw pixels, HoG and deep learning VGG-Face. The proposed ASRC framework is shown to outperform the conventional SRC in terms of recognition accuracy, in addition to other existing sparse-based methods and blur invariant methods at medium to high levels of distortion, when particularly used with discriminative features.
In order to assess the quality of features in improving both the sparsity of the representation and the classification accuracy, a feature sparse coding and classification index (FSCCI) is proposed and used for feature ranking and selection within both the SRC and ASRC frameworks.
The second part of the dissertation presents a method for unconstrained ear recognition using deep learning features. The unconstrained ear recognition is performed using transfer learning with deep neural networks (DNNs) as a feature extractor followed by a shallow classifier. Data augmentation is used to improve the recognition performance by augmenting the training dataset with image transformations. The recognition performance of the feature extraction models is compared with an ensemble of fine-tuned networks. The results show that, in the case where long training time is not desirable or a large amount of data is not available, the features from pre-trained DNNs can be used with a shallow classifier to give a comparable recognition accuracy to the fine-tuned networks.
ContributorsMounsef, Jinane (Author) / Karam, Lina (Thesis advisor) / Papandreou-Suppapola, Antonia (Committee member) / Li, Baoxin (Committee member) / Ren, Fengbo (Committee member) / Arizona State University (Publisher)
Created2018
Description
The purpose of this project was to construct and write code for an Internet-of-Things (IoT) based smart pet feeder to promote owner involvement in the health of their pets through the Internet to combat the high rate of obesity in pets in the United States. To achieve this, a pet feeder was developed to track the weight of the pet as well as how much food the pet eats while allowing the owner to see video of their pet eating, all through the owner's smartphone. In this thesis, current pet feeder strengths and weaknesses were researched, pet owners were surveyed, prototype features were decided upon, physical prototype components were purchased, a physical model of the pet feeder was developed in SolidWorks, a prototype was manufactured, and existing IoT libraries were utilized to develop code.
ContributorsCoote, Gabriela Phyllis (Author) / Ren, Fengbo (Thesis director) / Shrivastava, Aviral (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12