A survey of scan-capture power reduction techniques

With the advent of sub-nanometer geometries, integrated circuits (ICs) are required to be checked for newer defects. While scan-based architectures help detect these defects using newer fault models, test data inflation happens, increasing test time and test cost. An automatic test pattern generator (ATPG) exercise’s multiple fault sites simultaneously to reduce test data which causes elevated switching activity during the capture cycle. The switching activity results in an IR drop exceeding the devices under test (DUT) specification. An increase in IR-drop leads to failure of the patterns and may cause good DUTs to fail the test. The problem is severe during at-speed scan testing, which uses a functional rated clock with a high frequency for the capture operation. Researchers have proposed several techniques to reduce capture power. They used various methods, including the reduction of switching activity. This paper reviews the recently proposed techniques. The principle, algorithm, and architecture used in them are discussed, along with key advantages and limitations. In addition, it provides a classification of the techniques based on the method used and its application. The goal is to present a survey of the techniques and prepare a platform for future development in capture power reduction during scan testing

The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems

Scenario-based testing for the safety validation of highly automated vehicles is a promising approach that is being examined in research and industry. This approach heavily relies on data from real-world scenarios to derive the necessary scenario information for testing. Measurement data should be collected at a reasonable effort, contain naturalistic behavior of road users and include all data relevant for a description of the identified scenarios in sufficient quality. However, the current measurement methods fail to meet at least one of the requirements. Thus, we propose a novel method to measure data from an aerial perspective for scenario-based validation fulfilling the mentioned requirements. Furthermore, we provide a large-scale naturalistic vehicle trajectory dataset from German highways called highD. We evaluate the data in terms of quantity, variety and contained scenarios. Our dataset consists of 16.5 hours of measurements from six locations with 110 000 vehicles, a total driven distance of 45 000 km and 5600 recorded complete lane changes. The highD dataset is available online at: http://www.highD-dataset.comComment: IEEE International Conference on Intelligent Transportation Systems (ITSC) 201

VLSI Testing and Test Power

This paper first reviews the basics of VLSI testing, focusing on test generation and design for testability. Then it discusses the impact of test power in scan testing, and highlights the need for low-power VLSI testing.2011 International Green Computing Conference and Workshops (IGCC 2011), July 25-28, 2011, Orlando, FL, US

Effective Launch-to-Capture Power Reduction for LOS Scheme with Adjacent-Probability-Based X-Filling

It has become necessary to reduce power during LSI testing. Particularly, during at-speed testing, excessive power consumed during the Launch-To-Capture (LTC) cycle causes serious issues that may lead to the overkill of defect-free logic ICs. Many successful test generation approaches to reduce IR-drop and/or power supply noise during LTC for the launch-off capture (LOC) scheme have previously been proposed, and several of X-filling techniques have proven especially effective. With X-filling in the launch-off shift (LOS) scheme, however, adjacent-fill (which was originally proposed for shift-in power reduction) is used frequently. In this work, we propose a novel X-filling technique for the LOS scheme, called Adjacent-Probability-based X-Filling (AP-fill), which can reduce more LTC power than adjacent-fill. We incorporate AP-fill into a post-ATPG test modification flow consisting of test relaxation and X-filling in order to avoid the fault coverage loss and the test vector count inflation. Experimental results for larger ITC\u2799 circuits show that the proposed AP-fill technique can achieve a higher power reduction ratio than 0-fill, 1-fill, and adjacent-fill.2011 Asian Test Symposium, 20-23 November 2011, New Delhi, Indi

SANTO: Social Aerial NavigaTion in Outdoors

In recent years, the advances in remote connectivity, miniaturization of electronic components and computing power has led to the integration of these technologies in daily devices like cars or aerial vehicles. From these, a consumer-grade option that has gained popularity are the drones or unmanned aerial vehicles, namely quadrotors. Although until recently they have not been used for commercial applications, their inherent potential for a number of tasks where small and intelligent devices are needed is huge. However, although the integrated hardware has advanced exponentially, the refinement of software used for these applications has not beet yet exploited enough. Recently, this shift is visible in the improvement of common tasks in the field of robotics, such as object tracking or autonomous navigation. Moreover, these challenges can become bigger when taking into account the dynamic nature of the real world, where the insight about the current environment is constantly changing. These settings are considered in the improvement of robot-human interaction, where the potential use of these devices is clear, and algorithms are being developed to improve this situation. By the use of the latest advances in artificial intelligence, the human brain behavior is simulated by the so-called neural networks, in such a way that computing system performs as similar as possible as the human behavior. To this end, the system does learn by error which, in an akin way to the human learning, requires a set of previous experiences quite considerable, in order for the algorithm to retain the manners. Applying these technologies to robot-human interaction do narrow the gap. Even so, from a bird's eye, a noticeable time slot used for the application of these technologies is required for the curation of a high-quality dataset, in order to ensure that the learning process is optimal and no wrong actions are retained. Therefore, it is essential to have a development platform in place to ensure these principles are enforced throughout the whole process of creation and optimization of the algorithm. In this work, multiple already-existing handicaps found in pipelines of this computational gauge are exposed, approaching each of them in a independent and simple manner, in such a way that the solutions proposed can be leveraged by the maximum number of workflows. On one side, this project concentrates on reducing the number of bugs introduced by flawed data, as to help the researchers to focus on developing more sophisticated models. On the other side, the shortage of integrated development systems for this kind of pipelines is envisaged, and with special care those using simulated or controlled environments, with the goal of easing the continuous iteration of these pipelines.Thanks to the increasing popularity of drones, the research and development of autonomous capibilities has become easier. However, due to the challenge of integrating multiple technologies, the available software stack to engage this task is restricted. In this thesis, we accent the divergencies among unmanned-aerial-vehicle simulators and propose a platform to allow faster and in-depth prototyping of machine learning algorithms for this drones

Optimizing Test Pattern Generation Using Top-Off ATPG Methodology for Stuck–AT, Transition and Small Delay Defect Faults

The ever increasing complexity and size of digital circuits complemented by Deep Sub Micron (DSM) technology trends today pose challenges to the efficient Design For Test (DFT) methodologies. Innovation is required not only in designing the digital circuits, but also in automatic test pattern generation (ATPG) to ensure that the pattern set screens all the targeted faults while still complying with the Automatic Test Equipment (ATE) memory constraints. DSM technology trends push the requirements of ATPG to not only include the conventional static defects but also to include test patterns for dynamic defects. The current industry practices consider test pattern generation for transition faults to screen dynamic defects. It has been observed that just screening for transition faults alone is not sufficient in light of the continuing DSM technology trends. Shrinking technology nodes have pushed DFT engineers to include Small Delay Defect (SDD) test patterns in the production flow. The current industry standard ATPG tools are evolving and SDD ATPG is not the most economical option in terms of both test generation CPU time and pattern volume. New techniques must be explored in order to ensure that a quality test pattern set can be generated which includes patterns for stuck-at, transition and SDD faults, all the while ensuring that the pattern volume remains economical. This thesis explores the use of a “Top-Off” ATPG methodology to generate an optimal test pattern set which can effectively screen the required fault models while containing the pattern volume within a reasonable limit

Algorithms for Power Aware Testing of Nanometer Digital ICs

At-speed testing of deep-submicron digital very large scale integrated (VLSI) circuits has become mandatory to catch small delay defects. Now, due to continuous shrinking of complementary metal oxide semiconductor (CMOS) transistor feature size, power density grows geometrically with technology scaling. Additionally, power dissipation inside a digital circuit during the testing phase (for test vectors under all fault models (Potluri, 2015)) is several times higher than its power dissipation during the normal functional phase of operation. Due to this, the currents that flow in the power grid during the testing phase, are much higher than what the power grid is designed for (the functional phase of operation). As a result, during at-speed testing, the supply grid experiences unacceptable supply IR-drop, ultimately leading to delay failures during at-speed testing. Since these failures are specific to testing and do not occur during functional phase of operation of the chip, these failures are usually referred to false failures, and they reduce the yield of the chip, which is undesirable. In nanometer regime, process parameter variations has become a major problem. Due to the variation in signalling delays caused by these variations, it is important to perform at-speed testing even for stuck faults, to reduce the test escapes (McCluskey and Tseng, 2000; Vorisek et al., 2004). In this context, the problem of excessive peak power dissipation causing false failures, that was addressed previously in the context of at-speed transition fault testing (Saxena et al., 2003; Devanathan et al., 2007a,b,c), also becomes prominent in the context of at-speed testing of stuck faults (Maxwell et al., 1996; McCluskey and Tseng, 2000; Vorisek et al., 2004; Prabhu and Abraham, 2012; Potluri, 2015; Potluri et al., 2015). It is well known that excessive supply IR-drop during at-speed testing can be kept under control by minimizing switching activity during testing (Saxena et al., 2003). There is a rich collection of techniques proposed in the past for reduction of peak switching activity during at-speed testing of transition/delay faults ii in both combinational and sequential circuits. As far as at-speed testing of stuck faults are concerned, while there were some techniques proposed in the past for combinational circuits (Girard et al., 1998; Dabholkar et al., 1998), there are no techniques concerning the same for sequential circuits. This thesis addresses this open problem. We propose algorithms for minimization of peak switching activity during at-speed testing of stuck faults in sequential digital circuits under the combinational state preservation scan (CSP-scan) architecture (Potluri, 2015; Potluri et al., 2015). First, we show that, under this CSP-scan architecture, when the test set is completely specified, the peak switching activity during testing can be minimized by solving the Bottleneck Traveling Salesman Problem (BTSP). This mapping of peak test switching activity minimization problem to BTSP is novel, and proposed for the first time in the literature. Usually, as circuit size increases, the percentage of don’t cares in the test set increases. As a result, test vector ordering for any arbitrary filling of don’t care bits is insufficient for producing effective reduction in switching activity during testing of large circuits. Since don’t cares dominate the test sets for larger circuits, don’t care filling plays a crucial role in reducing switching activity during testing. Taking this into consideration, we propose an algorithm, XStat, which is capable of performing test vector ordering while preserving don’t care bits in the test vectors, following which, the don’t cares are filled in an intelligent fashion for minimizing input switching activity, which effectively minimizes switching activity inside the circuit (Girard et al., 1998). Through empirical validation on benchmark circuits, we show that XStat minimizes peak switching activity significantly, during testing. Although XStat is a very powerful heuristic for minimizing peak input-switchingactivity, it will not guarantee optimality. To address this issue, we propose an algorithm that uses Dynamic Programming to calculate the lower bound for a given sequence of test vectors, and subsequently uses a greedy strategy for filling don’t cares in this sequence to achieve this lower bound, thereby guaranteeing optimality. This algorithm, which we refer to as DP-fill in this thesis, provides the globally optimal solution for minimizing peak input-switching-activity and also is the best known in the literature for minimizing peak input-switching-activity during testing. The proof of optimality of DP-fill in minimizing peak input-switching-activity is also provided in this thesis

DP-fill: a dynamic programming approach to X-filling for minimizing peak test power in scan tests

At-speed testing is crucial to catch small delay defects that occur during the manufacture of high performance digital chips. Launch-Off-Capture (LOC) and Launch-Off-Shift (LOS) are two prevalently used schemes for this purpose. LOS scheme achieves higher fault coverage while consuming lesser test time over LOC scheme, but dissipates higher power during the capture phase of the at-speed test. Excessive IR-drop during capture phase on the power grid causes false delay failures leading to significant yield reduction that is unwarranted. As reported in literature, an intelligent filling of don't care bits (X-filling) in test cubes has yielded significant power reduction. Given that the tests output by automatic test pattern generation (ATPG) tools for big circuits have large number of don't care bits, the X-filling technique is very effective for them. Assuming that the design for testability (DFT) scheme preserves the state of the combinational logic between capture phases of successive patterns, this paper maps the problem of optimal X-filling for peak power minimization during LOS scheme to a variant of interval coloring problem and proposes a dynamic programming (DP) algorithm for the same along with a theoretical proof for its optimality. To the best of our knowledge, this is the first ever reported X-filling algorithm that is optimal. The proposed algorithm when experimented on ITC99 benchmarks produced peak power savings of up to 34% over the best known low power X-filling algorithm for LOS testing. Interestingly, it is observed that the power savings increase with the size of the circuit