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    Towards digital circuit approximation by exploiting fault simulation

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    In the recent years, Approximate Computing (AxC) has emerged as a new paradigm for energy efficient design of Integrated Circuits (ICs). AxC is based on the intuitive observation that, while performing exact computation requires a high amount of resources, allowing a selective approximation or an occasional relaxation of the specifications can provide significant gains in area, performances and energy efficiency. This work focuses on a case study about functional approximation of digital circuits. The functional approximation aims at modifying the circuit structure so that the original function F will be replaced by G whose implementation leads to area/energy reduction at the cost of reduced accuracy (i.e., some errors can be observed at the outputs of G). In this paper, we investigate an approach for the functional approximation exploiting fault simulation. Preliminary results show the potentiality of this approach in terms of area reduction

    A Test Pattern Generation Technique for Approximate Circuits Based on an ILP-Formulated Pattern Selection Procedure

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    Intrinsic resiliency of many today's applications opens new design opportunities. Some computation accuracy loss within the so-called resilient kernels does not affect the global quality of results. This has led the scientific community to introduce the approximate computing paradigm that exploits such a concept to boost computing system performances. By applying approximation to different layers, it is possible to design more efficient systems-in terms of energy, area, and performance-at the cost of a slight accuracy loss. In particular, at hardware level, this led to approximate integrated circuits. From the test perspective, this particular class of integrated circuits leads to new challenges. On the other hand, it also offers the opportunity of relaxing test constraints at the cost of a careful selection of so-called approximation-redundant faults. Such faults are classified as tolerable because of the slight introduced error. It follows that improvements in yield and test-cost reduction can be achieved. Nevertheless, conventional automatic test pattern generation (ATPG) algorithms, when not aware of the introduced approximation, generate test vectors covering approximation-redundant faults, thus reducing the yield gain. In this work, we show experimental evidence of such problem and present a novel ATPG technique to deal with it. Then, we extensively evaluate the proposed technique, and show that we are able to achieve an average yield improvement ranging from 19% up to 36%-compared to conventional ATPG-in terms of approximation-redundant fault coverage reduction. In some cases, the improvement can reach up to 100%

    A Survey of Testing Techniques for Approximate Integrated Circuits

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    Approximate computing (AxC) is increasingly emerging as a new design paradigm to produce more efficient computation systems by judiciously reducing the computation quality. In particular, AxC has been successfully applied to integrated circuits (ICs), in the last years. Hence, concerning the test of such new class of ICs, namely approximate ICs (AxICs), new challenges - as well as new opportunities - have emerged. In this survey, we provide a thorough analysis of issues related to test procedures for AxICs and review the state-of-the-art techniques to deal with them. We resort to an illustrative example having the twofold aim of: 1) guiding the reader through the AxIC testing challenges and 2) illustrating the existing solutions to correctly overcome them, while suitably taking advantage of opportunities coming from approximation. We analyze experimentally the most recent testing techniques for AxICs and highlight their mature aspects, as well as their shortcomings. Experimental outcomes show that the testing process for AxIC is not completely mature. Indeed, only under specific conditions existing testing procedures achieve good results

    On the comparison of different atpg approaches for approximate integrated circuits

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    Approximate Computing (AxC) emerges more and more as a new paradigm for the design of energy-efficient Integrated Circuits (ICs) at the cost of accuracy reduction. The latter has to be modeled and quantified by means of Error Metrics. From the testing point of view, AxC Integrated Circuits offer an opportunity. Instead of testing for all manufacturing defects, the goal is to test only for those that will lead to an error considered as not acceptable by the adopted Error Metrics. The main advantages are the test cost reduction, since the number of required test vectors will be reduced, and the yield improvement. We developed three approaches for generating test vectors targeting AxC Integrated Circuits. This paper aims at comparing these approaches on a public benchmark suite

    Testing approximate digital circuits: Challenges and opportunities

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    Approximate Computing (AxC) is based on the observation that a significant class of applications can inherently tolerate a certain amount of errors (i.e., the output quality is still acceptable to the user). AxC exploits this characteristic in order to apply selective approximations or occasional relaxations of the specifications. The benefit is a significant gain in energy efficiency and area reduction for Integrated Circuits (ICs). During the mission-mode, the IC can be affected by faults caused by environmental perturbations (e.g., radiations, electromagnetic interference), or aging-related phenomena. These faults may be propagated through the IC structure to the outputs and thus lead to observable errors. These errors (due to faults) may worsen the accuracy reduction - already introduced by the AxC - and possibly lead it to become unacceptable. This paper aims at investigating the challenges and the opportunities related to the test of AxC ICs

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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