Yiorgos Makris

University of Texas at Dallas, Richardson, Texas, United States

Are you Yiorgos Makris?

Claim your profile

Publications (138)51.35 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: The notion of Architectural Vulnerability Factor (AVF) has been extensively used to evaluate various aspects of design robustness. While AVF has been a very popular way of assessing element resiliency, its calculation requires rigorous and extremely time-consuming experiments. Furthermore, recent radiation studies in 90 nm and 65 nm technology nodes demonstrate that up to 55 percent of Single Event Upsets (SEUs) result in Multiple Bit Upsets (MBUs), and thus the Single Bit Flip (SBF) model employed in computing AVF needs to be reassessed. In this paper, we present a method for calculating the vulnerability of modern microprocessors -using Statistical Fault Injection (SFI)- several orders of magnitude faster than traditional SFI techniques, while also using more realistic fault models which reflect the existence of MBUs. Our method partitions the design into various hierarchical levels and systematically performs incremental fault injections to generate vulnerability estimates. The presented method has been applied on an Intel microprocessor and an Alpha 21264 design, accelerating fault injection by 15×, on average, and reducing computational cost for investigating the effect of MBUs. Extensive experiments, focusing on the effect of MBUs in modern microprocessors, corroborate that the SBF model employed by current vulnerability estimation tools is not sufficient to accurately capture the increasing effect of MBUs in contemporary processes.
    IEEE Transactions on Computers 09/2015; 64(9):2664-2674. DOI:10.1109/TC.2014.2375232 · 1.47 Impact Factor
  • Ke Huang · Yu Liu · Nenad Korolija · John M. Carulli · Yiorgos Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: We introduce two statistical methods for identifying recycled integrated circuits (ICs) through the use of one-class classifiers and degradation curve sensitivity analysis. Both methods rely on statistically learning the parametric behavior of known new devices and using it as a reference point to determine whether a device under authentication has previously been used. The proposed methods are evaluated using actual measurements and simulation data from digital and analog devices, with experimental results confirming their effectiveness in distinguishing between new and aged ICs and their superiority over previously proposed methods.
    IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 06/2015; 34(6):1-1. DOI:10.1109/TCAD.2015.2409267 · 1.20 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents statistical methods to identify and take advantage of correlations in the test methods and wafer-level spatial correlations among devices. The result, shown for industrial designs, is a far more optimized test suite.
    IEEE Design and Test 02/2015; 32(1):53-60. DOI:10.1109/MDAT.2014.2361721 · 1.14 Impact Factor
  • M. Maniatakos · M. K. Michael · Y. Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: We propose a technology-independent vulnerability-driven parity selection method for protecting modern microprocessor in-core memory arrays against multiple-bit upsets (MBUs). As MBUs constitute over 50% of the upsets in recent technologies, error correcting codes or physical interleaving are typically employed to effectively protect out-of-core memory structures, such as caches. Such methods, however, are not applicable to high performance in-core arrays, due to computational complexity, high delay, and area overhead. Therefore, we investigate vulnerability-based parity forest formation as an effective mechanism for detecting errors. Checkpointing and pipeline flushing can subsequently be used for correction. As the optimal parity tree construction for MBU detection is a computationally complex problem, an integer linear program formulation is introduced. In addition, vulnerability-based interleaving (VBI) is explored as a mechanism for further enhancing in-core array resiliency in constrained, single parity tree cases. VBI first physically disperses bitlines based on their vulnerability factor and then applies selective parity to these lines. Experimental results on Alpha 21264 and Intel P6 in-core memory arrays demonstrate that the proposed parity tree selection and VBI methods can achieve vulnerability reduction up to 86%, even when a small number of bits are added to the parity trees.
    IEEE Transactions on Very Large Scale Integration (VLSI) Systems 11/2014; DOI:10.1109/TVLSI.2014.2365032 · 1.14 Impact Factor
  • Dzmitry Maliuk · Yiorgos Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: We discuss the design of an experimentation platform intended for prototyping low-cost analog neural networks for on-chip integration with analog/RF circuits. The objective of such integration is to support various tasks, such as self-test, self-tuning, and trust/aging monitoring, which require classification of analog measurements obtained from on-chip sensors. Particular emphasis is given to cost-efficient implementation reflected in: 1) low energy and area budgets of circuits dedicated to neural networks; 2) robust learning in presence of analog inaccuracies; and 3) long-term retention of learned functionality. Our chip consists of a reconfigurable array of synapses and neurons operating below threshold and featuring sub- μW power consumption. The synapse circuits employ dual-mode weight storage: 1) a dynamic mode, for fast bidirectional weight updates during training and 2) a nonvolatile mode, for permanent storage of learned functionality. We discuss a robust learning strategy, and we evaluate the system performance on several benchmark problems, such as the XOR2-6 and two-spirals classification tasks.
    IEEE transactions on neural networks and learning systems 09/2014; 26(8). DOI:10.1109/TNNLS.2014.2354406 · 4.37 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: As the electronic component supply chain grows more complex due to globalization, with parts coming from a diverse set of suppliers, counterfeit electronics have become a major challenge that calls for immediate solutions. Currently, there are a few standards and programs available that address the testing for such counterfeit parts. However, not enough research has yet addressed the detection and avoidance of all counterfeit parts—recycled, remarked, overproduced, cloned, out-of-spec/defective, and forged documentation—currently infiltrating the electronic component supply chain. Even if they work initially, all these parts may have reduced lifetime and pose reliability risks. In this tutorial, we will provide a review of some of the existing counterfeit detection and avoidance methods. We will also discuss the challenges ahead for implementing these methods, as well as the development of new detection and avoidance mechanisms.
    Proceedings of the IEEE 08/2014; 102(8):1207-1228. DOI:10.1109/JPROC.2014.2332291 · 5.47 Impact Factor
  • Yu Liu · Ke Huang · Yiorgos Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: Statistical side channel fingerprinting is a popular hardware Trojan detection method, wherein a parametric signature of a chip is collected and compared to a trusted region in a multi-dimensional space. This trusted region is statistically established so that, despite the uncertainty incurred by process variations, the fingerprint of Trojan-free chips is expected to fall within this region while the fingerprint of Trojan-infested chips is expected to fall outside. Learning this trusted region, however, assumes availability of a small set of trusted (i.e. "golden") chips. Herein, we rescind this assumption and we demonstrate that an almost equally effective trusted region can be learned through a combination of a trusted simulation model, measurements from process control monitors (PCMs) which are typically present either on die or on wafer kerf, and advanced statistical tail modeling techniques. Effectiveness of this method is evaluated using silicon measurements from two hardware Trojan-infested versions of a wireless cryptographic integrated circuit.
  • Dzmitry Maliuk · Yiorgos Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: We introduce an analog non-volatile neural network chip which serves as an experimentation platform for prototyping custom classifiers for on-chip integration towards fully standalone built-in self-test (BIST) solutions for RF circuits. Our chip consists of a reconfigurable array of synapses and neurons operating below threshold and featuring sub-μW power consumption. The synapse circuits employ dynamic weight storage for fast bidirectional weight updates during training. The learned weights are then copied onto analog floating gate (FG) memory for permanent storage. The chip architecture supports two learning models: a multilayer perceptron and an ontogenic neural network. A benchmark XOR task is first employed to evaluate the overall learning capability of our chip. The BIST-related effectiveness is then evaluated on two case studies: the detection of parametric and catastrophic faults in an LNA and an RF front-end circuits, respectively.
    Design Automation and Test in Europe; 01/2014
  • [Show abstract] [Hide abstract]
    ABSTRACT: We present a nonintrusive concurrent error detection (CED) method for protecting the control logic of a contemporary floating-point unit (FPU). The proposed method is based on the observation that control logic errors lead to extensive data path corruption and affect, with high probability, the exponent part of the IEEE-754 floating-point representation. Thus, exponent monitoring can be utilized to detect errors in the control logic of the FPU. Predicting the exponent involves relatively simple operations; therefore, our method incurs significantly lower overhead than the classical approach of duplicating the control logic of the FPU. Indeed, experimental results on the openSPARC T1 processor using SPEC2006FP benchmarks show that as compared to control logic duplication, which incurs an area overhead of 17.9 percent of the FPU size, our method incurs an area overhead of only 5.8 percent yet still achieves detection of over 93 percent of transient errors in the FPU control logic. Moreover, the proposed method offers the ancillary benefit of also detecting 98.1 percent of the data path errors that affect the exponent, which cannot be detected via duplication of control logic. Finally, when combined with a classical residue code-based method for the fraction, our method leads to a complete CED solution for the entire FPU which provides a coverage of 94.1 percent of all errors at an area cost of 16.32 percent of the FPU size.
    IEEE Transactions on Computers 07/2013; 62(7):1376-1388. DOI:10.1109/TC.2012.81 · 1.47 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Modern microprocessors incorporate a variety of architectural features, such as branch prediction and speculative execution, which are not critical to the correctness of their operation yet are essential towards improving performance. Accordingly, while faults in the corresponding hardware may not necessarily affect functional correctness, they may, nevertheless, adversely impact performance. In this paper, we investigate quantitatively the performance impact of such faults using a superscalar, dynamically-scheduled, out-of-order, Alpha-like microprocessor, on which we execute SPEC2000 integer benchmarks. We provide extensive fault simulation-based experimental results that elucidate the various aspects of performance faults and we discuss how this information may guide the inclusion of additional hardware for performance loss recovery and yield enhancement.
    Journal of Electronic Testing 06/2013; 29(3):351-366. DOI:10.1007/s10836-013-5360-5 · 0.43 Impact Factor
  • Yier Jin · Bo Yang · Yiorgos Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: We propose a new information assurance model which can dynamically track the information flow in circuit designs and hence protect sensitive data from malicious leakage. Relying on the Coq proof assistant platform, the new model maps register transfer level (RTL) codes written in hardware description languages (HDLs) into structural Coq representatives by assigning all input, output, and internal signal sensitivity levels. The signal sensitivity levels can be dynamically adjusted after each clock cycle based on proposed signal sensitivity transition rules. The development of data secrecy properties and theorem generation functions makes the translation process from security properties to Coq theorems independent of target circuits and, for the first time, makes it possible to construct a property library, facilitating (semi) automation of the proof. The proposed cycle accurate information assurance scheme is successfully demonstrated on cryptographic circuits with various complexities from a small-scale DES encryption core to a state-of-the-art AES encryption design prohibiting the leakage of sensitive information caused by hardware Trojans inserted in RTL codes.
    2013 IEEE International Symposium on Hardware-Oriented Security and Trust (HOST); 06/2013
  • Ke Huang · Nathan Kupp · John M. Carulli · Yiorgos Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: In an effort to reduce the cost of specification testing in analog/RF circuits, spatial correlation modeling of wafer-level measurements has recently attracted increased attention. Existing approaches for capturing and leveraging such correlation, however, rely on the assumption that spatial variation is smooth and continuous. This, in turn, limits the effectiveness of these methods on actual production data, which often exhibits localized spatial discontinuous effects. In this work, we propose a novel approach which enables spatial correlation modeling of wafer-level analog/RF tests to handle such effects and, thereby, to drastically reduce prediction error for measurements exhibiting discontinuous spatial patterns. The core of the proposed approach is a k-means algorithm which partitions a wafer into k clusters, as caused by discontinuous effects. Individual correlation models are then constructed within each cluster, revoking the assumption that spatial patterns should be smooth and continuous across the entire wafer. Effectiveness of the proposed approach is evaluated on industrial probe test data from more than 3,400 wafers, revealing significant error reduction over existing approaches.
    Design, Automation & Test in Europe Conference & Exhibition (DATE), 2013; 01/2013
  • [Show abstract] [Hide abstract]
    ABSTRACT: Many of the design companies cannot afford owning and acquiring expensive foundries and hence, go fabless and outsource their design fabrication to foundries that are potentially untrustwrothy. This globalization of Integrated Circuit (IC) design flow has introduced security vulnerabilities. If a design is fabricated in a foundry that is outside the direct control of the (fabless) design house, reverse engineering, malicious circuit modification, and Intellectual Property (IP) piracy are possible. In this tutorial, we elaborate on these and similar hardware security threats by making connections to VLSI testing. We cover design-for-trust techniques, such as logic encryption, aging acceleration attacks, and statistical methods that help identify Trojan'ed and counterfeit ICs.
    Test Symposium (ETS), 2013 18th IEEE European; 01/2013
  • Y. Jin · D. Maliuk · Y. Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: The use of side-channel parametric measurements along with statistical analysis methods for detecting hardware Trojans in fabricated integrated circuits has been studied extensively in recent years, initially for digital designs but recently also for their analog/RF counterparts. Such post-fabrication trust evaluation methods, however, are unable to detect dormant hardware Trojans which are activated after a circuit is deployed in its field of operation. For the latter, an on-chip trust evaluation method is required. To this end, we present a general architecture for post-deployment trust evaluation based on on-chip classifiers. Specifically, we discuss the design of an on-chip analog neural network which can be trained to distinguish trusted from untrusted circuit functionality based on simple measurements obtained via on-chip measurement acquisition sensors. The proposed method is demonstrated using a Trojan-free and two Trojan-infested variants of a wireless cryptographic IC design, as well as a fabricated programmable neural network experimentation chip. As corroborated by the obtained experimental results, two current measurements suffice for the on-chip classifier to effectively assess trustworthiness and, thereby, detect hardware Trojans that are activated after chip deployment.
    On-Line Testing Symposium (IOLTS), 2013 IEEE 19th International; 01/2013
  • M. Maniatakos · M.K. Michael · Y. Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: We investigate the complexity and utility of performing Multiple Bit Upset (MBU) vulnerability analysis in modern microprocessors. While the Single Bit Flip (SBF) model constitutes the prevailing mechanism for capturing the effect of Single Event Upsets (SEUs) due to alpha particle or neutron strikes in semiconductors, recent radiation studies in 90nm and 65nm technology nodes demonstrate that up to 55% of such strikes result in Multiple Bit Upsets (MBUs). Consequently, the accuracy of popular vulnerability analysis methods, such as the Architecural Vulnerability Factor (AVF) and Failures In Time (FIT) rate estimates based on the SBF assumption comes into question, especially in modern microprocessors which contain a significant amount of memory elements. Towards alleviating this concern, we present an extensive infrastructure which enables MBU vulnerability analysis in modern microprocessors. Using this infrastructure and a modern microprocessor model, we perform a large scale MBU vulnerability analysis study and we report two key findings: (i) the SBF fault model overestimates vulnerability by up to 71%, as compared to a more realistic modeling and distribution of faults in the 90nm and 65nm processes, and (ii) the rank-ordered lists of critical bits, as computed through the SBF and MBU models, respectively, are very similar, as indicated by the average rank difference of a bit which is less than 1.45%.
    On-Line Testing Symposium (IOLTS), 2013 IEEE 19th International; 01/2013
  • Yier Jin · Y. Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: We introduce a proof-carrying based framework for assessing the trustworthiness of third-party hardware Intellectual Property (IP), particularly geared toward microprocessor cores. This framework enables definition of and formal reasoning on security properties, which, in turn, are used to certify the genuineness and trustworthiness of the instruction set and, by extension, are used to prevent insertion of malicious functionality in the Hardware Description Language (HDL) code of an acquired microprocessor core. Security properties and trustworthiness proofs are derived based on a new formal hardware description language (formal-HDL), which is developed as part of the framework along with conversion rules to/from other HDLs to enable general applicability to IP cores independent of coding language. The proposed framework, along with the ability of a sample set of pertinent security properties to detect malicious IP modifications, is demonstrated on an 8051 microprocessor core.
    Computer-Aided Design (ICCAD), 2013 IEEE/ACM International Conference on; 01/2013
  • Ke Huang · J.M. Carulli · Y. Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: As the supply chain of electronic circuits grows more complex, with parts coming from different suppliers scattered across the globe, counterfeit integrated circuits (ICs) are becoming a serious challenge which calls for immediate solutions. Counterfeiting includes re-labeling legitimate chips or illegitimately replicating chips and deceptively selling them as made by the legitimate manufacturer, or simply selling fake chips. Counterfeiting also includes providing defective parts or simply previously used parts recycled from scrapped assemblies. Obviously, there is a multitude of legal and financial implications involved in such activities and even if these devices initially work, they may have reduced lifetime and may pose reliability risks. In this tutorial, we provide a comprehensive review of existing techniques which seek to prevent and/or detect counterfeit integrated circuits. Various approaches are discussed and an advanced machine learning-based method employing parametric measurements is described in detail.
    Test Conference (ITC), 2013 IEEE International; 01/2013
  • Ke Huang · N. Kupp · J.M. Carulli · Y. Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: Monitoring the semiconductor manufacturing process and understanding the various sources of variation and their repercussions is a crucial capability. Indeed, identifying the root-cause of device failures, enhancing yield of future production through improvement of the manufacturing environment, and providing feedback to the designer toward development of design techniques that minimize failure rate rely on such a capability. To this end, we introduce a spatial decomposition method for breaking down the variation of a wafer to its spatial constituents, based on a small number of measurements sampled across the wafer. We demonstrate that by leveraging domain-specific knowledge and by using as constituents dynamically learned, interpretable basis functions, the ability of the proposed method to accurately identify the sources of variation is drastically improved, as compared to existing approaches. We then illustrate the utility of the proposed spatial variation decomposition method in (i) identifying the main contributor to yield variation, (ii) predicting the actual yield of a wafer, and (iii) clustering wafers for production planning and abnormal wafer identification purposes. Results are reported on industrial data from high-volume manufacturing, confirming the ability of the proposed method to provide great insight regarding the sources of variation in the semiconductor manufacturing process.
    Test Conference (ITC), 2013 IEEE International; 01/2013
  • Michail Maniatakos · Maria K. Michael · Yiorgos Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: We propose an AVF-driven parity selection method for protecting modern microprocessor in-core memory arrays against MBUs. As MBUs constitute more than 50% of the upsets in latest technologies, error correcting codes or physical interleaving are typically employed to effectively protect out-of-core memory structures, such as caches. However, such methods are not applicable to high-performance in-core arrays, due to computational complexity, high delay and area overhead. To this end, we revisit parity as an effective mechanism to detect errors and we resort to pipeline flushing and checkpointing for correction. We demonstrate that optimal parity tree construction for MBU detection is a computationally complex problem, which we then formulate as an integer-linear-program (ILP). Experimental results on Alpha 21264 and Intel P6 in-core memory arrays demonstrate that optimal parity tree selection can achieve great vulnerability reduction, even when a small number of bits are added to the parity trees, compared to simple heuristics. Furthermore, the ILP formulation allows us to find better solutions by effectively exploring the solution space in the presence of multiple parity trees; results show that the presence of 2 parity trees offers a vulnerability reduction of more than 50% over a single parity tree.
    Design, Automation & Test in Europe Conference & Exhibition (DATE), 2013; 01/2013
  • Ke Huang · N. Kupp · J.M. Carulli · Y. Makris
    [Show abstract] [Hide abstract]
    ABSTRACT: Statistical intra-die correlation has been extensively studied as a means for reducing test cost in analog/RF ICs. Generally known as alternate test, this approach seeks to predict the performances of an analog/RF chip based on low-cost measurements on the same chip and statistical models learned from a training set of chips. Recently, an orthogonal direction for leveraging statistical correlation towards reducing test cost of analog/RF ICs has also gained traction. Specifically, inter-die spatial correlation models learned from specification tests on a sparse subset of die on a wafer are used to predict performances on the unobserved die. In this work, we investigate the potential of combining these two statistical approaches, anticipating that the performance prediction accuracy of the joint correlation model will surpass the accuracy of its constituents. Experimental results on industrial semiconductor manufacturing data validate this conjecture and corroborate the utility of the combined performance prediction models.
    Test Symposium (ETS), 2013 18th IEEE European; 01/2013

Publication Stats

1k Citations
51.35 Total Impact Points

Institutions

  • 2011–2015
    • University of Texas at Dallas
      • Department of Electrical Engineering
      Richardson, Texas, United States
  • 2013
    • University of Central Florida
      Orlando, Florida, United States
  • 2001–2012
    • Yale University
      • Department of Electrical Engineering
      New Haven, Connecticut, United States
  • 2008
    • University of Tehran
      Teheran, Tehrān, Iran
    • French National Centre for Scientific Research
      Lutetia Parisorum, Île-de-France, France
    • Kuwait University
      • Department of Computer Engineering
      Kuwait, Muhafazat al `Asimah, Kuwait
  • 2006
    • Yale-New Haven Hospital
      New Haven, Connecticut, United States
    • University of New Haven
      New Haven, Connecticut, United States
  • 2003
    • Rensselaer Polytechnic Institute
      • Department of Computer Science
      Троя, New York, United States
  • 1999–2000
    • California State University
      • College of Engineering & Computer Sciences
      Long Beach, California, United States
    • University of California, San Diego
      • Department of Computer Science and Engineering (CSE)
      San Diego, California, United States