24,860 research outputs found

    A Strategy Language for Testing Register Transfer Level Logic

    Get PDF
    The development of modern ICs requires a huge investment in RTL verification. This is a reflection of brisk release schedules and the complexity of contemporary chip designs. A major bottleneck to reaching verification closure in such designs is the disproportionate effort expended in crafting directed tests; which is necessary to reach those behaviors that other, more automated testing methods fail to cover. This paper defines a novel language that can be used to generate targeted stimuli for RTL logic and which mitigates the complexities of writing directed tests. The main idea is to treat directed testing as a meta-reasoning problem about simulation. Our language is both formalized and prototyped as a proof-search strategy language in rewriting logic. We illustrate its novel features and practical use with several examples.published or submitted for publicatio

    Balancing Scalability and Uniformity in SAT Witness Generator

    Full text link
    Constrained-random simulation is the predominant approach used in the industry for functional verification of complex digital designs. The effectiveness of this approach depends on two key factors: the quality of constraints used to generate test vectors, and the randomness of solutions generated from a given set of constraints. In this paper, we focus on the second problem, and present an algorithm that significantly improves the state-of-the-art of (almost-)uniform generation of solutions of large Boolean constraints. Our algorithm provides strong theoretical guarantees on the uniformity of generated solutions and scales to problems involving hundreds of thousands of variables.Comment: This is a full version of DAC 2014 pape

    Evolution of associative learning in chemical networks

    Get PDF
    Organisms that can learn about their environment and modify their behaviour appropriately during their lifetime are more likely to survive and reproduce than organisms that do not. While associative learning – the ability to detect correlated features of the environment – has been studied extensively in nervous systems, where the underlying mechanisms are reasonably well understood, mechanisms within single cells that could allow associative learning have received little attention. Here, using in silico evolution of chemical networks, we show that there exists a diversity of remarkably simple and plausible chemical solutions to the associative learning problem, the simplest of which uses only one core chemical reaction. We then asked to what extent a linear combination of chemical concentrations in the network could approximate the ideal Bayesian posterior of an environment given the stimulus history so far? This Bayesian analysis revealed the ’memory traces’ of the chemical network. The implication of this paper is that there is little reason to believe that a lack of suitable phenotypic variation would prevent associative learning from evolving in cell signalling, metabolic, gene regulatory, or a mixture of these networks in cells

    A perturbation analysis of spontaneous action potential initiation by stochastic ion channels

    Get PDF
    A stochastic interpretation of spontaneous action potential initiation is developed for the Morris- Lecar equations. Initiation of a spontaneous action potential can be interpreted as the escape from one of the wells of a double well potential, and we develop an asymptotic approximation of the mean exit time using a recently-developed quasi-stationary perturbation method. Using the fact that the activating ionic channel’s random openings and closings are fast relative to other processes, we derive an accurate estimate for the mean time to fire an action potential (MFT), which is valid for a below-threshold applied current. Previous studies have found that for above-threshold applied current, where there is only a single stable fixed point, a diffusion approximation can be used. We also explore why different diffusion approximation techniques fail to estimate the MFT
    • …
    corecore