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STRONGLY CONNECTED COMPONENTS AND STEADY STATES IN GENE REGULATORY NETWORKSMILES, RICHARD BRENT January 2007 (has links)
No description available.
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The Creation of Solid Models of the Human Knee from Magnetic Resonance ImagesFening, Stephen D. 27 June 2003 (has links)
No description available.
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Probability of Solvability of Random Systems of 2-Linear Equations over <i>GF</i>(2)Yeum, Ji-A January 2008 (has links)
No description available.
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Boolean networks as modeling frameworkGreil, Florian 29 July 2022 (has links)
In a network, the components of a given system are represented as nodes, the interactions
are abstracted as links between the nodes. Boolean networks refer to a class of
dynamics on networks, in fact it is the simplest possible dynamics where each node has
a value 0 or 1. This allows to investigate extensively the dynamics both analytically and by
numerical experiments. The present article focuses on the theoretical concept of relevant
components and their immediate application in plant biology. References for more in-depth
treatment of the mathematical details are also given.
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Sufficiency-based Filtering of Invariants for Sequential Equivalence CheckingHu, Wei 14 February 2011 (has links)
Verification, as opposed to Testing and Post-Silicon Validation, is a critical step for Integrated Circuits (IC) Design, answering the question "Are we designing the right function?" before the chips are manufactured. One of the core areas of Verification is Equivalence Checking (EC), which is a special yet independent case of Model Checking (MC). Equivalence Checking aims to prove that two circuits, when fed with the same inputs, produce the exact same outputs. There are broadly two ways to conduct Equivalence Checking, simulation and Formal Equivalence Checking. Simulation requires one to try out different input combinations and observe if the two circuits produce the same output. Obviously, since it is not possible to enumerate all combinations of different inputs, completeness cannot be guaranteed. On the other hand, Formal Equivalence Checking can achieve 100% confidence. As the number of gates and in particular, the number of flip-flops, in circuits has grown tremendously during the recent years, the problem of Formal Equivalence Checking has become much harder â A recent evaluation of a general-case Formal Equivalence Checking engine [1] shows that about 15% of industrial designs cannot be verified after a typical sequential synthesis flow. As a result, a lot of attention on Formal Equivalence Checking has been drawn both academically and industrially.
For years Combinational Equivalence Checking(CEC) has been the pervasive framework for Formal Equivalence Checking(FEC) in the industry. However, due to the limitation of being able to verify circuits only with 1:1 flip-flop pairing, a pure CEC-based methodology requires a full regression of the verification process, meaning that performing sequential optimizations like retiming or FSM re-encoding becomes somewhat of a bottleneck in the design cycle [2]. Therefore, a more powerful framework — Sequential Equivalence Checking (SEC) — has been gradually adopted in industry.
In this thesis, we target on Sequential Equivalence Checking by finding efficient yet powerful group of relationships (invariants) among the signals of the two circuits being compared. In order to achieve a high success rate on some of the extremely hard-to-verify circuits, we are interested in both two-node and multi-node (up to 4 nodes) invariants. Also we are interested in invariants among both flip-flops and internal signals. For large circuits, there can be too many potential invariants requiring much time to prove. However, we observed that a large portion of them may not even contribute to equivalence checking. Moreover, equivalence checking can be significantly helped if there exists a method to check if a subset of potential invariants would be sufficient (e.g., whether two-nodes are enough or multi-nodes are also needed) prior to the verification step. Therefore, we propose two sufficiency-based approaches to identify useful invariants out of the initial potential invariants for SEC. Experimental results show that our approach can either demonstrate insufficiency of the invariants or select a small portion of them to successfully prove the equivalence property.
Our approaches are quite case-independent and flexible. They can be applied on circuits with different synthesis techniques and combined with other techniques. / Master of Science
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Enhancing SAT-based Formal Verification Methods using Global LearningArora, Rajat 25 May 2004 (has links)
With the advances in VLSI and System-On-Chip (SOC) technology, the complexity of hardware systems has increased manifold. Today, 70% of the design cost is spent in verifying these intricate systems. The two most widely used formal methods for design verification are Equivalence Checking and Model Checking. Equivalence Checking requires that the implementation circuit should be exactly equivalent to the specification circuit (golden model). In other words, for each possible input pattern, the implementation circuit should yield the same outputs as the specification circuit. Model checking, on the other hand, checks to see if the design holds certain properties, which in turn are indispensable for the proper functionality of the design. Complexities in both Equivalence Checking and Model Checking are exponential to the circuit size.
In this thesis, we firstly propose a novel technique to improve SAT-based Combinational Equivalence Checking (CEC) and Bounded Model Checking (BMC). The idea is to perform a low-cost preprocessing that will statically induce global signal relationships into the original CNF formula of the circuit under verification and hence reduce the complexity of the SAT instance. This efficient and effective preprocessing quickly builds up the implication graph for the circuit under verification, yielding a large set of logic implications composed of direct, indirect and extended backward implications. These two-node implications (spanning time-frame boundaries) are converted into two-literal clauses, and added to the original CNF database. The added clauses constrain the search space of the SAT-solver engine, and provide correlation among the different variables, which enhances the Boolean Constraint Propagation (BCP). Experimental results on large and difficult ISCAS'85, ISCAS'89 (full scan) and ITC'99 (full scan) CEC instances and ISCAS'89 BMC instances show that our approach is independent of the state-of-the-art SAT-solver used, and that the added clauses help to achieve more than an order of magnitude speedup over the conventional approach. Also, comparison with Hyper-Resolution [Bacchus 03] suggests that our technique is much more powerful, yielding non-trivial clauses that significantly simplify the SAT instance complexity.
Secondly, we propose a novel global learning technique that helps to identify highly non-trivial relationships among signals in the circuit netlist, thereby boosting the power of the existing implication engine. We call this new class of implications as 'extended forward implications', and show its effectiveness through additional untestable faults they help to identify.
Thirdly, we propose a suite of lemmas and theorems to formalize global learning. We show through implementation that these theorems help to significantly simplify a generic CNF formula (from Formal Verification, Artificial Intelligence etc.) by identifying the necessary assignments, equivalent signals, complementary signals and other non-trivial implication relationships among its variables. We further illustrate through experimental results that the CNF formula simplification obtained using our tool outshines the simplification obtained using other preprocessors. / Master of Science
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Sequential Equivalence Checking with Efficient Filtering Strategies for Inductive InvariantsNguyen, Huy 24 May 2011 (has links)
Powerful sequential optimization techniques can drastically change the Integrated Circuit (IC) design paradigm. Due to the limited capability of sequential verification tools, aggressive sequential optimization is shunned nowadays as there is no efficient way to prove the preservation of equivalence after optimization. Due to the fact that the number of transistors fitting on single fixed-size die increases with Moore's law, the problem gets harder over time and in an exponential rate. It is no surprise that functional verification becomes a major bottleneck in the time-to-market of a product. In fact, literature has reported that 70% of design time is spent on making sure the design is bug-free and operating correctly. One of the core verification tasks in achieving high quality products is equivalence checking. Essentially, equivalence checking ensures the preservation of optimized product's functionality to the unoptimized model. This is important for industry because the products are modified constantly to meet different goals such as low power, high performance, etc. The mainstream in conducting equivalence checking includes simulation and formal verification. In simulation approach, golden design and design under verification (DUV) are fed with same stimuli for input expecting outputs to produce identical responses. In case of discrepancy, traces will be generated and DUV will undergo modifications. With the increase in input pins and state elements in designs, exhaustive simulation becomes infeasible. Hence, the completeness of the approach is not guaranteed and notions of coverage has to be accompanied. On the other hand, formal verification incorporates mathematical proofs and guarantee the completeness over the search space. However, formal verification has problems of its own in which it is usually resource intensive. In addition, not all design can be verified after optimization processes. That is to say the golden model and DUV are vastly different in structure which cause modern checker to give inconclusive result. Due to this nature, this thesis focuses in improving the strength and the efficiency of sequential equivalence checking (SEC) using formal approach.
While there has been great strides made in the verification for combinational circuits, SEC still remains rather rudimentary. Without powerful SEC as a backbone, aggressive sequential synthesis and optimization are often avoided if the optimized design cannot be proved to be equivalent to the original one. In an attempt to take on the challenges of SEC, we propose two frameworks that successfully determining equivalence for hard-to-verify circuits. The first framework utilizes arbitrary relations between any two nodes within the two sequential circuits in question. The two nodes can reside in the same or across the circuits; likewise, they can be from the same time-frame or across time-frames. The merit for this approach is to use global structure of the circuits to speed up the verification process. The second framework introduces techniques to identify subset but yet powerful multi-node relations (involve more than 2 nodes) which then help to prune large don't care search space and result in a successful SEC framework. In contrast with previous approaches in which exponential number of multi-node relations are mined and learned, we alleviate the computation cost by selecting much fewer invariants to achieve desired conclusion. Although independent, the two frameworks could be used in sequential to complement each other. Experimental results demonstrate that our frameworks can take on many hard-to-verify cases and show a significant speed up over previous approaches. / Master of Science
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Fast Static Learning and Inductive Reasoning with Applications to ATPG ProblemsDsouza, Michael Dylan 03 March 2015 (has links)
Relations among various nodes in the circuit, as captured by static and inductive invariants, have shown to have a positive impact on a wide range of EDA applications. Techniques such as boolean constraint propagation for static learning and assume-then-verify approach to reason about inductive invariants have been possible due to efficient SAT solvers. Although a significant amount of research effort has been dedicated to the development of effective invariant learning techniques over the years, the computation time for deriving powerful multi-node invariants is still a bottleneck for large circuits. Fast computation of static and inductive invariants is the primary focus of this thesis. We present a novel technique to reduce the cost of static learning by intelligently identifying redundant computations that may not yield new invariants, thereby achieving significant speedup. The process of inductive invariant reasoning relies on the assume-then-verify framework, which requires multiple iterations to complete, making it infeasible for cases with a large set of multi-node invariants. We present filtering techniques that can be applied to a diverse set of multi-node invariants to achieve a significant boost in performance of the invariant checker. Mining and reasoning about all possible potential multi-node invariants is simply infeasible. To alleviate this problem, strategies that narrow down the focus on specific types of powerful multi-node invariants are also presented. Experimental results reflect the promise of these techniques. As a measure of quality, the invariants are utilized for untestable fault identification and to constrain ATPG for path delay fault testing, with positive results. / Master of Science
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Exterior calculus and fermionic quantum computationVourdas, Apostolos 20 September 2018 (has links)
Yes / Exterior calculus with its three operations meet, join and hodge star complement, is used for the representation of fermion-hole systems and for fermionic analogues of logical gates. Two different schemes that implement fermionic quantum computation, are proposed. The first scheme compares fermionic gates with Boolean gates, and leads to novel electronic devices that simulate fermionic gates. The second scheme uses a well known map between fermionic and multi-qubit systems, to simulate fermionic gates within multi-qubit systems.
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Developing Integrated DNA Molecular CircuitsBardales Martinez, Andrea C 01 January 2024 (has links) (PDF)
Due to nucleic acid’s programmability, it is possible to realize DNA structures with computing functions, and thus a new generation of molecular computers is evolving to solve biological and medical problems. There is evidence that genetic heredity diseases and cancer can be the result of genetic heterogeneity, thus there is a need for diagnostics and therapeutic tools with multiplex and smart components to compute all the molecular drivers. DNA molecular computers mimics electronic computers by programming synthetic nucleic acids to perform similarly to central processing units. Considering how the evolution of integrated circuits made possible the revolution of silicon-based computers, integrated DNA molecular circuits can be developed to allow modular designing and scale to complex DNA nano-processors. This dissertation covers the development of four-way junction (4J) DNA logic gates that can be wired to result in functionally complete gates, and their immobilization on a modular DNA board that serves as a scaffold for logic gate integration, fast signal processing, and cascading. Connecting 4J DNA logic gates YES and NOT resulted in OR, NAND, and IMPLY logic circuits; the three circuits can operate under the input of miRNAs, either oncogenic or/and tumor-suppressors, and give two possible diagnoses: healthy or cancerous. The DNA board can expand as the DNA circuit grows in the number of integrated 4J units. Signal propagation across a wired of 4J YES logic gates showed signal completion in < 3 min, accounting for a signal propagation rate of 4.5 nm/min and that up to 6 units can be cascaded before the signal dissipates. Lastly, an approach to chemically ligate all oligonucleotide components of the DNA molecular device is presented, in which we also found a route for the bioconjugation of 5’ to 5’ and 3’ to 3’ oligonucleotides.
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