Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimized VM memory allocation based on monitored cache hit ratio

Cloud computing by the use of virtual machines has become increasingly important in various situations. In such an environment, multiple virtual machines run on a single physical machine. Many hypervisor implementations have a ballooning function. This function enables virtual machine memory size to be dynamically changed at runtime. Hence, it is expected that dynamic memory resource management while considering the application loads can improve its performance. In particular, I/O performance is expected to be improved significantly because it strongly depends on the size of the HDD cache in an operating system, e.g., a page cache in Linux. The Xen hypervisor has xenballoon, which dynamically changes the size of the virtual machine memory based on the size of memory consumed by the processes in the virtual machines and does not consider the size of the page cache. Therefore, the I/O performance is not improved. In a study, a method for adjusting virtual machine memory size was proposed. However, it assumes applications to be homogeneous. In this paper, we propose a method for dynamic management of virtual machine memory size without assumption for applications. The method takes into account the page cache hit ratio. We show the performance evaluation of the method for various read/write applications. The experimental results demonstrate that our method can improve performance of I/O intensive applications in virtual machines.
EyeSeeX: Visualization of Out-of-View Objects on Small Field-of-View Augmented and Virtual Reality Devices

Recent advances in Virtual and Augmented Reality technology enable a variety of new applications (e.g., multi-player games in real environments). However, current devices suffer from having small fields of view, making the process of locating spatially distributed digital content similar to looking through a keyhole. In this work, we present EyeSeeX as a technique for visualizing out-of-view objects with head-mounted devices. EyeSeeX improves upon our previously developed technique EyeSee360 for small field-of-view (FOV) devices. To do so, EyeSeeX proposes two strategies: (1) reducing the visualized field and (2) compressing the presented information. Further, EyeSeeX supports video and optical see-through Augmented Reality, Mixed Reality, and Virtual Reality devices.
Heterogeneous Wireless Charger Placement with Obstacles

This paper considers the problem of Heterogeneous wIreless charger Placement with Obstacles (HIPO), i.e., given a number of heterogeneous rechargeable devices distributed on a 2D plane where obstacles of arbitrary shapes exist, deploying heterogeneous chargers with a given cardinality of each type, i.e., determining their positions and orientations, the combination of which we name as strategies, on the plane such that the rechargeable devices achieve maximized charging utility. After presenting our practical directional charging model, we first propose to use a piecewise constant function to approximate the nonlinear charging power, and divide the whole area into multi-feasible geometric areas in which a certain type of chargers have constant approximated charging power. Next, we propose the Practical Dominating Coverage Set extraction algorithm to reduce the unlimited solution space to a limited one by exacting a finite set of candidate strategies for all multi-feasible geometric areas. Finally, we prove the problem falls in the realm of maximizing a monotone submodular function subject to a partition matroid constraint, which allows a greedy algorithm to solve with approximation ratio of 1/2 -- ϵ. We conduct both simulations and field experiments to evaluate the performance of our algorithm and other five comparison algorithms. The results show that our algorithm outperforms the comparison algorithms by at least 33.49% on average.
Conversion of PDF documents into HTML: a case study of document image analysis

Portable document format (PDF) has become the de facto standard in many fields because of its independence of local formatting restrictions and its accurate reproducibility. On the other hand, HTML documents are becoming an integral form of our lives by being the dominant form for information exchange within the World Wide Web environment. This paper discusses how image-processing techniques can be used to perform document layout analysis of complex multiple-column PDF documents. This analysis allows the conversion of these documents into the HTML format keeping the logical and physical layout intact.
Validation de la notion de similarité textuelle dans un cadre multilingue

We propose in this contribution a method to validate the relevance of the notion of vector based semantic similarity, using a multilingual framework. The goal is to verify that vector based semantic similarities can be reliably transfered from one language to another. More precisely, the idea is to test whether the relative positions of documents in a vector space associated with a given source language are close to the ones of their translations in the vector space associated with the target language. The experiments have been conducted using the standard Vector Space model and the DSIR model. The method used for this test can also be applied to the automated evaluation of the performance of machine translation systems or to multilingual information retrieval.
Hardening Hypervisors against Vulnerabilities in Instruction Emulators

Vulnerabilities in hypervisors are crucial in multi-tenant clouds and attractive for attackers because a vulnerability in the hypervisor can undermine all the virtual machine (VM) security. This paper focuses on vulnerabilities in instruction emulators inside hypervisors. Vulnerabilities in instruction emulators are not rare; CVE-2017-2583, CVE-2016-9756, CVE-2015-0239, CVE-2014-3647, to name a few. For backward compatibility with legacy x86 CPUs, conventional hypervisors emulate arbitrary instructions at any time if requested. This design leads to a large attack surface, making it hard to get rid of vulnerabilities in the emulator. This paper proposes FWinst that narrows the attack surface against vulnerabilities in the emulator. The key insight behind FWinst is that the emulator should emulate only a small subset of instructions, depending on the underlying CPU micro-architecture and the hypervisor configuration. FWinst recognizes emulation contexts in which the instruction emulator is invoked, and identifies a legitimate subset of instructions that are allowed to be emulated in the current context. By filtering out illegitimate instructions, FWinst narrows the attack surface. In particular, FWinst is effective on recent x86 micro-architectures because the legitimate subset becomes very small. Our experimental results demonstrate FWinst prevents existing vulnerabilities in the emulator from being exploited on Westmere micro-architecture, and the runtime overhead is negligible.
Energy-Efficient Speculative Execution using Advanced Reservation for Heterogeneous Clusters

Many Big Data processing applications nowadays run on large-scale multi-tenant clusters. Due to hardware heterogeneity and resource contentions, straggler problem has become the norm rather than the exception in such clusters. To handle the straggler problem, speculative execution has emerged as one of the most widely used straggler mitigation techniques. Although a number of speculative execution mechanisms have been proposed, as we have observed from real-world traces, the questions of "when" and "where" to launch speculative copies have not been fully discussed and hence cause inefficiencies on the performance and energy of Big Data applications. In this paper, we propose a performance model and an energy consumption model to reveal the performance and energy variations with different speculative execution solutions. We further propose a window-based dynamic resource reservation and a heterogeneity-aware copy allocation technique to answer the "when" and "where" questions for speculative executions. Evaluations using real-world traces show that our proposed technique can improve the performance of Big Data applications by up to 30% and reduce the overall energy consumption by up to 34%.
Studying the Novice Programmer

Parallel to the growth of computer usage in society is the growth of programming instruction in schools. This informative volume unites a wide range of perspectives on the study of novice programmers that will not only inform readers of empirical findings, but will also provide insights into how novices reason and solve problems within complex domains. The large variety of methodologies found in these studies helps to improve programming instruction and makes this an invaluable reference for researchers planning studies of their own. Topics discussed include historical perspectives, transfer, learning, bugs, and programming environments.
Learning board evaluation function for Othello by hybridizing coevolution with temporal difference learning

Hybridization of global and local search techniques has already produced promising results in the fields of optimization and machine learning. It is commonly presumed that approaches employing this idea, like memetic algorithms that combine evolutionary algorithms with local search, benefit from complementary characteristics of constituent methods and maintain the right balance between exploration and exploitation of the search space. While such extensions of evolutionary algorithms have been intensively studied, hybrids of local search with coevolutionary algorithms have not received much attention yet. In this paper we attempt to fill this gap by presenting Coevolutionary Temporal Difference Learning (CTDL) that works by interlacing global search provided by competitive coevolution and local search by means of temporal difference learning. We verify CTDL by applying it to the board game of Othello, where it learns board evaluation functions represented by a linear architecture of weighted piece counter. The results of a computational experiment show CTDL’s superiority when compared to coevolutionary algorithm and temporal difference learning alone, both in terms of performance of elaborated strategies and computational cost. In order to further exploit CTDL’s potential, we also extend it by an archive that keeps track of selected well-performing solutions found so far and uses them to improve search convergence. The overall conclusion is that the fusion of various forms of coevolution with a gradient-based local search can be highly beneficial and deserves further research.
Declarative debugging for lazy functional languages

Lazy functional languages are declarative and allow the programmer to write programs where operational issues such as the evaluation order are left implicit. It is desirable to maintain a declarative view also during debugging so as to avoid burdening the programmer with operational details, for example concerning the actual evaluation order which tends to be difficult to follow. Conventional debugging techniques focus on the operational behaviour of a program and thus do not constitute a suitable foundation for a general-purpose debugger for lazy functional languages. Yet, the only readily available, general-purpose debugging tools for this class of languages are simple, operational tracers.This thesis presents a technique for debugging lazy functional programs declaratively and an efficient implementation of a declarative debugger for a large subset of Haskell. As far as we know, this is the first implementation of such a debugger which is sufficiently efficient to be useful in practice. Our approach is to construct a declarative trace which hides the operational details, and then use this as the input to a declarative (in our case algorithmic) debugger.The main contributions of this thesis are:A basis for declarative debugging of lazy functional programs is developed in the form of a trace which hides operational details. We call this kind of trace the Evaluation Dependence Tree (EDT). We show how to construct EDTs efficiently in the context of implementations of lazy functional languages based on graph reduction. Our implementation shows that the time penalty for tracing is modest, and that the space cost can be kept below a user definable limit by storing one portion of the EDT at a time.Techniques for reducing the size of the EDT are developed based on declaring modules to be trusted and designating certain functions as starting-points for tracing.We show how to support source-level debugging within our framework. A large subset of Haskell is handled, including list comprehensions.Language implementations are discussed from a debugging perspective, in particular what kind of support a debugger needs from the compiler and the run-time system.We present a working reference implementation consisting of a compiler for a large subset of Haskell and an algorithmic debugger. The compiler generates fairly good code, also when a program is compiled for debugging, and the resource consumption during debugging is modest. The system thus demonstrates the feasibility of our approach.
Cross-layer design for wireless networks

As the cellular and PCS world collides with wireless LANs and Internet-based packet data, new networking approaches will support the integration of voice and data on the composite infrastructure of cellular base stations and Ethernet-based wireless access points. This article highlights some of the past accomplishments and promising research avenues for an important topic in the creation of future wireless networks. We address the issue of cross-layer networking, where the physical and MAC layer knowledge of the wireless medium is shared with higher layers, in order to provide efficient methods of allocating network resources and applications over the Internet. In essence, future networks will need to provide "impedance matching" of the instantaneous radio channel conditions and capacity needs with the traffic and congestion conditions found over the packet-based world of the Internet. Furthermore, such matching will need to be coordinated with a wide range of particular applications and user expectations, making the topic of cross-layer networking increasingly important for the evolving wireless buildout.
Distributed spatial data management

The complexity of spatial data management will be high as the volume of spatial data increases rapidly. As the emerging technology, it is an innovative method that grid computing technology is applied to manage geographically distributed, autonomous and heterogeneous spatial data. Integrating grid computing with spatial data management technology, the authors designed a basic but high extensible framework for managing distributed and large-scale spatial data. In this paper we put emphasis upon spatial metadata service design and spatial data grid design.
3CAuth - A Novel Multi-Factor Authentication Scheme Using QR-Code

A multi factor authentication scheme called ’3C-Auth’ is proposed in this paper. The scheme carries out a comprehensive authentication process using the smart card, secret-pin, registered ﬁnger print, and registered mobile number of the user. The user’s password is neither transmitted in plaintext form nor revealed to the authentication server. The scheme is shone to be proof against phishing, password guessing, replay, or stolen-veriﬁer attacks. Resistance to parallel session and denial of service attacks and the use of QR-Code in preference to SMS for OTP transfer together, make the scheme attractive for operation under peak loads. Integration of the “3C-Auth” into Multi-Layered Filtering (MLF) scheme leads to secure handling of peak loads on the server ensuring concurrency and availability as well. This clearly enhances the QoS in terms of making right admittance to right resources.
Language: Introductory Readings

Preface - PART ONE: LANGUAGE AND ITS STUDY - PART TWO: LANGUAGE AND ACQUISITION - PART THREE: LANGUAGE AND THE BRAIN - PART FOUR: PHONETICS, PHONOLOGY, AND MORPHOLOGY - PART FIVE: SYNTAX, SEMANTICS, AND DISCOURSE - PART SIX: LANGUAGE VARIATION: REGIONAL AND SOCIAL - PART SEVEN: HISTORICAL LINGUISTICS AND LANGUAGE CHANGE - PART EIGHT: BROADER PERSPECTIVES
Number of confirmation blocks for Bitcoin and GHOST consensus protocols on networks with delayed message delivery: Extended abstract

A specific number of transaction confirmation blocks determines average time of receiving and accepting payments at cryptocurrencies, and the shortest confirmation time for the same level of blockchain security provides the best user properties. Existing papers on transaction confirmation blocks for Bitcoin use implicit assumption of prompt spreading of Bitcoin blocks over the network (that is not always the case for the real world conditions). The newer publications with rigorous analysis and proofs of Bitcoin blockchain properties that take into account network delays provide asymptotic estimates, with no specific numbers for transaction confirmation blocks. We propose three methods for determination of required number of confirmation blocks for Bitcoin and GHOST on networks with delayed message delivery with different models that take into account the possibility of faster adversarial node syncronization. For the GHOST we propose the first (to our knowledge) strict theoretical method that allows to get required number of confirmation blocks for a given attacker's hashrate and attack success probability.
An architectural power optimization case study using high-level synthesis

Architectural power optimization offers significant power gains in addition to which can be obtained at higher and lower levels of abstraction. Although there has been some academic research for architectural power optimization, the commercial design automation technology is still in infancy and quite behind the current needs of the industry as many portable computing and communication products and greener non-portable products are being introduced into the market. In this paper we describe an environment for exploring low-power architectures using high-level synthesis, which is currently being used for production chip design until comprehensive commercialized alternatives are available. We also present the results and findings from experiments with a CCITT G.721 ADPCM Predictor design, which should benefit on-going research on automated solutions.
rvGAHP: push-based job submission using reverse SSH connections

Computational science researchers running large-scale scientific workflow applications often want to run their workflows on the largest available compute systems to improve time to solution. Workflow tools used in distributed, heterogeneous, high performance computing environments typically rely on either a push-based or a pull-based approach for resource provisioning from these compute systems. However, many large clusters have moved to two-factor authentication for job submission, making traditional automated push-based job submission impossible. On the other hand, pull-based approaches such as pilot jobs may lead to increased complexity and a reduction in node-hour efficiency. In this paper, we describe a new, efficient approach based on HTCondor-G called reverse GAHP (rvGAHP) that allows us to push jobs using reverse SSH submissions with better efficiency than pull-based methods. We successfully used this approach to perform a large probabilistic seismic hazard analysis study using SCEC's CyberShake workflow in March 2017 on the Titan Cray XK7 hybrid system at Oak Ridge National Laboratory.
Multiple-page translation for TLB

Traditional approaches for increasing TLB hit ratios include using more TLB entries and/or bigger page sizes. These techniques are often subject to significant costs in implementations. We illustrate techniques for improving TLB efficiency with less expensive hardware. The basic idea is to allow multiple pages translated upon each invocation of translation through page table. The proposal can improve TLB hit ratios with reasonable amount of hardware while transparent to the software. Trade-offs in using multiple page translations are illustrated through simulation results. <<ETX>>
Design & evaluation of the human-biometric sensor interaction method

This research examines how humans interact with biometric devices to provide the biometrics community with a comparative evaluation method that uses ergonomics, usability, and image quality criteria as explanatory variables of performance, which is based on the design of the sensor. Specifically, this research in the Human-Biometric Sensor Interaction has four primary objectives. First, analyze literature in the fields of: biometrics, ergonomics, HCI, and usability to determine what influences the interaction between the human and the biometric device and what aspects of these fields can be applied to the design of biometric devices. Second, develop a conceptual model for the design of biometric devices, specifically swipe-based fingerprint recognition and propose an evaluation method to assess the created form factors. Third, create two alternate swipe-based fingerprint form factors based on the conceptual model that includes: biomechanics and anthropometry of the hand and fingers, biometric literature, and focus groups and interviews to gather personal perceptions and common interaction problems for swipe based fingerprint recognition devices. Lastly, evaluate the commercially available and new form factor devices in a comparative performance evaluation using the proposed HBSI evaluation method. Results to date are revealed in the poster.
DIATEST: a fast diagnostic test pattern generator for combinational circuits

The authors present an efficient algorithm for the generation of diagnostic test patterns which distinguish between two arbitrary single stuck-at faults. The algorithm is able to extend a given set of test patterns which is generated from the viewpoint of fault detection to a diagnostic test pattern set with a diagnostic resolution down to a fault equivalence class. The difficult problem of identifying the equivalence of two faults, analogous to the problem of redundancy identification in ATPG, has been solved. The efficiency of the algorithm is demonstrated by experimental results for a set of benchmark circuits. DIATEST, the implementation of the algorithm, either generates diagnostic test patterns for all distinguishable pairs of faults or identifies pairs of faults as being equivalent for each of the benchmark circuits. <<ETX>>
Dynamic bounding of successor force computations in the force directed list scheduling algorithm

The well known Force Directed List Scheduling (FDLS) Algorithm uses a rigorous priority function called the Force of an operation. The force of an operation is governed by two components, namely the self-force of an operation and its successors' forces. The successor force in turn is governed by the self-force of all the descendants of the operation. FDLS is computationally intensive in its force calculations. For data flow dominated designs, a major portion of the FDLS execution time is spent in the computation of successor forces. However in this paper we observe that it is not always necessary to compute successor forces till the last successor level. We have shown in this paper that there usually exists a stabilization point after which successor force computations would not affect the quality of the schedule produced. This paper presents a concept of stability to show that it is possible to dynamically bound the successor force calculations in FDLS, up to a certain level of descendants. We have measured the performance of FDLS for a suite of high level synthesis benchmarks. Results presented in the paper show considerable reduction in execution time for the same schedule quality. This would allow a high-level synthesis tool to perform better design space exploration.