16,859 research outputs found

    Complexity, parallel computation and statistical physics

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    The intuition that a long history is required for the emergence of complexity in natural systems is formalized using the notion of depth. The depth of a system is defined in terms of the number of parallel computational steps needed to simulate it. Depth provides an objective, irreducible measure of history applicable to systems of the kind studied in statistical physics. It is argued that physical complexity cannot occur in the absence of substantial depth and that depth is a useful proxy for physical complexity. The ideas are illustrated for a variety of systems in statistical physics.Comment: 21 pages, 7 figure

    Artificial neural network model for arrival time computation in gate level circuits

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    Advances in the VLSI process technology lead to variations in the process parameters. These process variations severely affect the delay computation of a digital circuit. Under such variations, the various delays, i.e. net delay, gate delay, etc., are no longer deterministic. They are random in nature and are assumed to be probabilistic. They keep changing, based on factors such as process, voltage, temperature, and a few others. This calls for efficient tools to perform timing checks on a design. This work presents a technique to compute the arrival time of a digital circuit. The arrival time (AT) is computed using two different timing engines, namely, static timing analysis (STA) and statistical static timing analysis (SSTA). This work also aims to eliminate number of false paths. It uses a fast and efficient filtering method by utilizing ATPG stuck-at faults and path delay faults. ISCAS-89 benchmark circuits are used for implementation. The results obtained using the probabilistic approach are more accurate than the conventional STA. It has been verified with an Artificial Neural Network (ANN) model. The arrival time calculated using SSTA shows 7% improvement over that of STA. The absolute error is reduced twofold in the case of the ANN model for SSTA

    Doctor of Philosophy

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    dissertationThe design of integrated circuit (IC) requires an exhaustive verification and a thorough test mechanism to ensure the functionality and robustness of the circuit. This dissertation employs the theory of relative timing that has the advantage of enabling designers to create designs that have significant power and performance over traditional clocked designs. Research has been carried out to enable the relative timing approach to be supported by commercial electronic design automation (EDA) tools. This allows asynchronous and sequential designs to be designed using commercial cad tools. However, two very significant holes in the flow exist: the lack of support for timing verification and manufacturing test. Relative timing (RT) utilizes circuit delay to enforce and measure event sequencing on circuit design. Asynchronous circuits can optimize power-performance product by adjusting the circuit timing. A thorough analysis on the timing characteristic of each and every timing path is required to ensure the robustness and correctness of RT designs. All timing paths have to conform to the circuit timing constraints. This dissertation addresses back-end design robustness by validating full cyclical path timing verification with static timing analysis and implementing design for testability (DFT). Circuit reliability and correctness are necessary aspects for the technology to become commercially ready. In this study, scan-chain, a commercial DFT implementation, is applied to burst-mode RT designs. In addition, a novel testing approach is developed along with scan-chain to over achieve 90% fault coverage on two fault models: stuck-at fault model and delay fault model. This work evaluates the cost of DFT and its coverage trade-off then determines the best implementation. Designs such as a 64-point fast Fourier transform (FFT) design, an I2C design, and a mixed-signal design are built to demonstrate power, area, performance advantages of the relative timing methodology and are used as a platform for developing the backend robustness. Results are verified by performing post-silicon timing validation and test. This work strengthens overall relative timed circuit flow, reliability, and testability

    Advancing Hardware Security Using Polymorphic and Stochastic Spin-Hall Effect Devices

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    Protecting intellectual property (IP) in electronic circuits has become a serious challenge in recent years. Logic locking/encryption and layout camouflaging are two prominent techniques for IP protection. Most existing approaches, however, particularly those focused on CMOS integration, incur excessive design overheads resulting from their need for additional circuit structures or device-level modifications. This work leverages the innate polymorphism of an emerging spin-based device, called the giant spin-Hall effect (GSHE) switch, to simultaneously enable locking and camouflaging within a single instance. Using the GSHE switch, we propose a powerful primitive that enables cloaking all the 16 Boolean functions possible for two inputs. We conduct a comprehensive study using state-of-the-art Boolean satisfiability (SAT) attacks to demonstrate the superior resilience of the proposed primitive in comparison to several others in the literature. While we tailor the primitive for deterministic computation, it can readily support stochastic computation; we argue that stochastic behavior can break most, if not all, existing SAT attacks. Finally, we discuss the resilience of the primitive against various side-channel attacks as well as invasive monitoring at runtime, which are arguably even more concerning threats than SAT attacks.Comment: Published in Proc. Design, Automation and Test in Europe (DATE) 201

    Using genetic algorithms to generate test sequences for complex timed systems

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    The generation of test data for state based specifications is a computationally expensive process. This problem is magnified if we consider that time con- straints have to be taken into account to govern the transitions of the studied system. The main goal of this paper is to introduce a complete methodology, sup- ported by tools, that addresses this issue by represent- ing the test data generation problem as an optimisa- tion problem. We use heuristics to generate test cases. In order to assess the suitability of our approach we consider two different case studies: a communication protocol and the scientific application BIPS3D. We give details concerning how the test case generation problem can be presented as a search problem and automated. Genetic algorithms (GAs) and random search are used to generate test data and evaluate the approach. GAs outperform random search and seem to scale well as the problem size increases. It is worth to mention that we use a very simple fitness function that can be eas- ily adapted to be used with other evolutionary search techniques

    Delay Measurements and Self Characterisation on FPGAs

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    This thesis examines new timing measurement methods for self delay characterisation of Field-Programmable Gate Arrays (FPGAs) components and delay measurement of complex circuits on FPGAs. Two novel measurement techniques based on analysis of a circuit's output failure rate and transition probability is proposed for accurate, precise and efficient measurement of propagation delays. The transition probability based method is especially attractive, since it requires no modifications in the circuit-under-test and requires little hardware resources, making it an ideal method for physical delay analysis of FPGA circuits. The relentless advancements in process technology has led to smaller and denser transistors in integrated circuits. While FPGA users benefit from this in terms of increased hardware resources for more complex designs, the actual productivity with FPGA in terms of timing performance (operating frequency, latency and throughput) has lagged behind the potential improvements from the improved technology due to delay variability in FPGA components and the inaccuracy of timing models used in FPGA timing analysis. The ability to measure delay of any arbitrary circuit on FPGA offers many opportunities for on-chip characterisation and physical timing analysis, allowing delay variability to be accurately tracked and variation-aware optimisations to be developed, reducing the productivity gap observed in today's FPGA designs. The measurement techniques are developed into complete self measurement and characterisation platforms in this thesis, demonstrating their practical uses in actual FPGA hardware for cross-chip delay characterisation and accurate delay measurement of both complex combinatorial and sequential circuits, further reinforcing their positions in solving the delay variability problem in FPGAs
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