bluuebunny/crossref_metadata_2025 huggingface dataset:
A compact method for efficient evaluation of acoustic absorbers with submicron materials
Authors: Cai Xiaobing , Yang Jun
Published: December 2018

Materials with submicron or nano-scale features possess unique physical properties and are well-suited for application in noise reduction. To date, experimental characterization of the sound absorbing ability of the submicron/nano materials is still a challenging task, because the measuring of sound absorptivity usually requires bulky samples, while the preparation of large quantities of submicron/nano materials or structures is generally costly and laborious. In this work, an acoustic testing method is proposed to evaluate the acoustic absorptivity of submicron/nano materials using small samples. Based on the transfer-matrix algorithm, the method establishes correlations among acoustic-related parameters of a large sensor fixture and a small sample holder. A proof-of-principle experimental setup was developed to test absorbers with well-known acoustic behavior to verify accuracy of the method. Finally, the sound absorption properties of two submicron materials are characterized, with one comprising dispersed silver submicron fibers and the other comprising electrospinning submicron fibers. The results indicate that acoustic absorption coefficients can be effectively retrieved using only 1/200 of the amount of materials that are typically required in the standard test.
Bessel beam expansion of linear focused ultrasound
Authors: Daniel Timothy D. , Gittes Fred , Kirsteins Ivars P. , Marston Philip L.
Published: December 2018

Previous work on scattering by Bessel beams shows that expansion of incident sound fields in term of these beams has application to scattering [P. L. Marston, J. Acoust. Soc. Am. 122, 247–252 (2007)]. In this work, an expression for the expansion coefficients of propagating, axisymmetric, sound fields are derived. In this paper, this expression is applied to a linear focused axisymmetric sound field and is expanded in terms of Bessel beam components. This is done for focused beams radiated from a spherical cap source. A physical optics model is applied to sound propagation close to the source to facilitate the calculation of the Bessel beam expansion coefficients. This type of model is useful for focused scattering [P. L. Marston and D. S. Langley, J. Acoust. Soc. Am. 73, 1464–1475 (1983)]. Once the expansion coefficients are found, the sound field can be evaluated by superposition. The model agrees approximately with Chen, Schwarz, and Parker [J. Acoust. Soc. Am. 94, 2979–2991 (1993)] and O'Neil [J. Acoust. Soc. Am. 21, 516–526 (1949)] on axis and with direct integration of a Kirchhoff integral both on and off axis. This type of expansion will have applications to scattering problems.
Antibody-Mediated Protective Mechanisms Induced by a Trivalent Parainfluenza Virus-Vectored Ebolavirus Vaccine
Authors: Kimble J. Brian , Malherbe Delphine C. , Meyer Michelle , Gunn Bronwyn M. , Karim Marcus M. , Ilinykh Philipp A. , Iampietro Mathieu , Mohamed Khaled S. , Negi Surendra , Gilchuk Pavlo , Huang Kai , Wolf Yuri I. , Braun Werner , Crowe James E. , Alter Galit , Bukreyev Alexander
Published: December 2018

The symptoms of the disease caused by the ebolaviruses Ebola, Bundibugyo, and Sudan are similar, and their areas of endemicity overlap. However, because of the limited antigenic relatedness of the ebolavirus glycoprotein (GP) used in all candidate vaccines against these viruses, they protect only against homologous and not against heterologous ebolaviruses. Therefore, a broadly specific pan-ebolavirus vaccine is required, and this might be achieved by administration of a cocktail of vaccines. The effects of cocktail administration of ebolavirus vaccines on the antibody repertoire remain unknown. Here, an in-depth analysis of the antibody responses to administration of a cocktail of human parainfluenza virus type 3-vectored vaccines against individual ebolaviruses was performed, which included analysis of binding to GP, neutralization of individual ebolaviruses, epitope specificity, Fc-mediated functions, and protection against the three ebolaviruses. The results demonstrated potent and balanced responses against individual ebolaviruses and no significant reduction of the responses compared to that induced by individual vaccines.
Mapping the pH Sensors Critical for Host Cell Entry by a Complex Nonenveloped Virus
Authors: Wu Weining , Celma Cristina C. , Kerviel Adeline , Roy Polly
Published: December 2018

Virus entry into a susceptible cell is the first step of infection and a significant point at which infection can be prevented. To enter effectively, viruses must sense the cellular environment and, when appropriate, initiate a series of changes that eventually jettison the protective shell and deposit virus genes into the cytoplasm. Many viruses sense pH, but how this happens and the events that follow are often poorly understood. Here, we address this question for a large multilayered bluetongue virus. We show key residues in outer capsid proteins, a pH-sensing histidine of a zinc finger within the receptor-binding VP2 protein, and certain histidine residues in the membrane-penetrating VP5 protein that detect cellular pH, leading to irreversible changes and propel the virus through the cell membrane. Our data reveal a novel mechanism of cell entry for a nonenveloped virus and highlight mechanisms which may also be used by other viruses.
Inhibition of DNA-Sensing Pathway by Marek's Disease Virus VP23 Protein through Suppression of Interferon Regulatory Factor 7 Activation
Authors: Gao Li , Li Kai , Zhang Yu , Liu Yongzhen , Liu Changjun , Zhang Yanping , Gao Yulong , Qi Xiaole , Cui Hongyu , Wang Yongqiang , Wang Xiaomei
Published: December 2018

Despite widespread vaccination, Marek’s disease (MD) continues to pose major challenges for the poultry industry worldwide. MDV causes immunosuppression and deadly lymphomas in chickens, suggesting that this virus has developed a successful immune evasion strategy. However, little is known regarding the initiation and modulation of the host innate immune response during MDV infection. This study demonstrates that the cGAS-STING DNA-sensing pathway is critical for the induction of the IFN-β response against MDV infection in chicken fibroblasts and macrophages. An MDV protein, VP23, was found to efficiently inhibit the cGAS-STING pathway. VP23 selectively inhibits IRF7 but not NF-κB activation. VP23 interacts with IRF7 and blocks its binding to TBK1, thereby suppressing IRF7 activation and resulting in inhibition of the DNA-sensing pathway. These findings expand our knowledge of DNA sensing in chickens and reveal a mechanism through which MDV antagonizes the host IFN response.
The 13th International Double-Stranded RNA Virus Symposium, Houffalize, Belgium, 24 to 28 September 2018
Authors: Desselberger Ulrich
Published: December 2018

The triennial International Double-Stranded RNA Virus Symposium, this year organized by J. Matthijnssens, J.
Sudden-onset severe presyncope in a 67-year-old man
Authors: Sanders Katie Hannah , Martin Claire A , Virdee Munmohan
Published: December 2018

A 67-year-old man presented to the emergency department with sudden onset of severe presyncope. He reported that he had a permanent pacemaker implanted in 2006 following atrioventricular node ablation for persistent atrial fibrillation (AF). After suffering increasing shortness of breath, he underwent upgrade to cardiac resynchronisation therapy (CRT) in 2016. He denied any recent falls, interventions or changes in medication. ECG monitoring showed AF with a broad ventricular escape rhythm at around 25 bpm with pauses of up to 3 s. Placement of a magnet over the device resulted in pacing (figure 1A). The implanted device (Medtronic Syncra C2TR01) was interrogated (figure 1B), and a chest radiograph was obtained (figure 2).
Figure 1

(A) Twelve-lead ECG demonstrating intrinsic rhythm and pacing after application of magnet. (B) Device interrogation with right ventricular threshold test.

Figure 2

(C) Anteroposterior chest radiograph demonstrating lead position on admission.

Question

What was the cause of this presentation?

Noise oversensing on the right ventricular (RV) lead due to lead fracture.

The RV septal lead has displaced into the right atrial (RA).

RA and RV leads were switched in the can during the CRT upgrade.

Increase in threshold of RV and left ventricular (LV) leads resulting in loss of capture.
Multiorgan accelerated silicosis misdiagnosed as sarcoidosis in two workers exposed to quartz conglomerate dust
Authors: Guarnieri Gabriella , Bizzotto Rosana , Gottardo Ottorino , Velo Emanuela , Cassaro Mauro , Vio Stefania , Putzu Maria Grazia , Rossi Federica , Zuliani Paolo , Liviero Filippo , Mason Paola , Maestrelli Piero
Published: December 2018

Introduction

Clusters of silicosis cases have been reported in the fabrication of quartz conglomerate, a new high-silica-content artificial stone for kitchen and bathroom benchtops (countertops).

Aim

We describe two cases of accelerated-type silicosis with hepatic granulomas arising in workers exposed to artificial quartz conglomerates.

Methods

A confident diagnosis of multiorgan silicosis was based on high level of respirable silica in the workplace, typical radiological alterations in chest high-resolution CT, histological findings in the lung and liver, and detection of silica crystals in both tissues by phase-contrast polarising light microscopy and scanning electron microscopy and energy dispersive spectroscopy.

Results

The development of the disease <10 years after the first exposure is consistent with an accelerated-type of silicosis. Compared with other studies related to quartz conglomerate exposure, we determined that the levels of airborne crystalline silica during activity in the finishing area were between 0.260 and 0.744 mg/m3, that is, much higher than the threshold limit value according to American Conference of Governmental Industrial Hygienists (0.025 mg/m3). Moreover, liver granulomas were associated with accumulation of crystalline silica particles in the hepatic tissue.

Conclusions

Quartz conglomerate fabrication is a potentially dangerous occupation. General practitioners and physicians should have awareness of this newly described occupational hazard. Accurate occupational history is critical in avoiding misdiagnosis, as silicosis caused by inhalation of dust from artificial quartz conglomerates may exhibit atypical presentation. These features seem to be related to the extremely high level of silica exposure and, possibly, to an increased toxicity of the dust generated in this process.
Hydrophobic polythiophene hole-transport layers to address the moisture-induced decomposition problem of perovskite solar cells
Authors: Kundu Soumya , Kelly Timothy L.
Published: December 2018

Perovskite solar cells have emerged as one of the most promising next-generation photovoltaic technologies and have achieved a record power conversion efficiency of 22.7%. The technology meets industrial demands for cost effectiveness and scalability; however, the instability of lead halide perovskites toward moisture is a major barrier to their commercial development. Previous studies have revealed that the use of hydrophobic hole-transport layers (e.g., poly(3-hexylthiophene), P3HT) can slow the ingress of water vapor and improve the lifetime of the underlying perovskite, suggesting a route to longer lived devices. In this work, we report the synthesis of a variety of poly(3-alkoxythiophenes) with different side chains. The side chains range from hydrophilic (triethylene glycol methyl ether) to extremely hydrophobic (highly fluorinated hexyloxy). We evaluated the polymers, alongside commercially available P3HT, for their ability to stabilize methylammonium lead iodide films at high relative humidities. The fluorinated polythiophenes were able to substantially improve the perovskite lifetime, suggesting that more hydrophobic hole-transport layers may be a route to more stable perovskite solar cells.
Hollow bridge columns with triangular confining reinforcement
Authors: Kim Tae-Hoon , Kim Ick-Hyun , Lee Jae-Hoon , Shin Hyun Mock
Published: December 2018

The purpose of this study is to assess the structural performance of hollow bridge columns with triangular confining reinforcement. The proposed triangular reinforcement details were equal to the conventional reinforcement details in terms of required structural performance. The triangular confining reinforcement is also economically feasible and rational, and facilitate shorter construction periods. Three hollow cast-in-situ concrete and three precast concrete bridge columns were tested. The behavior of the hollow columns is discussed in terms of their lateral load-drift relationship, cumulative dissipated energy, and lateral load-strain curves. The nonlinear finite element analysis program RCAHEST (reinforced concrete analysis in higher evaluation system technology) was used to analyze hollow bridge columns, and adopted a modified joint element for the precast concrete bridge columns. The results showed that the proposed innovative reinforcement details were superior to the conventional reinforcement details, in terms of the required structural performance.
Formulating the behavior of thermal radiation and magnetic dipole effects on Darcy–Forchheimer grasped ferrofluid flow
Authors: Hussain Azad , Muneer Zainia , Malik M.Y. , Ali Shoaib
Published: December 2018

In this article a boundary layer analysis has been carried out to examine the Darcy–Forchheimer flow of Carreau ferrofluid through a sensor duct between two parallel plates. The top plate is assumed to be squeezed whereas the lower plate is at rest. Inspection has been accomplished in the occupancy of thermal radiation and magnetic dipole. Thermal conductivity is also considered, which is determined by temperature. After incorporating these speculations, dimensional equations supervising the flow and heat transfer distinctions are transfigured into a dimensionless system of differential equations by implementing similarity transformations. The result of squeezed flow index b, ferrohydrodynamic interaction β∗, porous medium permeability parameter S1, local inertia coefficient S2, Eckert number λ, Prandtl number Pr, Curie temperature g, and Weissenberg number We on velocity and temperature curves are observed. The numerical solution for boundary layer momentum and energy equations is obtained. The present analysis demonstrates that velocity profile significantly drops owing to a rise in Weissenberg number.
Somatic growth and the risks of bronchopulmonary dysplasia and pulmonary hypertension: connecting epidemiology and physiology
Authors: Underwood Mark A. , Wedgwood Stephen , Lakshminrusimha Satyan , Steinhorn Robin H.
Published: December 2018

In the premature infant, poor growth in utero (fetal growth restriction) and in the first weeks of life (postnatal growth restriction) are associated with increased risk for bronchopulmonary dysplasia and pulmonary hypertension. In this review, we summarize the epidemiologic data supporting these associations, present a novel rodent model of postnatal growth restriction, and review 5 promising mechanisms by which poor nutrition may affect the developing lung. These observations support the hypothesis that nutritional and (or) pharmacologic interventions early in life may be able to decrease risk of the pulmonary complications of extreme prematurity.
Decreased levels of miR-28-5p and miR-361-3p and increased levels of insulin-like growth factor 1 mRNA in mononuclear cells from patients with hereditary hemorrhagic telangiectasia
Authors: Cannavicci Anthony , Zhang Qiuwang , Dai Si-Cheng , Faughnan Marie E. , Kutryk Michael J.B.
Published: December 2018

Hereditary hemorrhagic telangiectasia (HHT) is a rare vascular disorder inherited in an autosomal dominant manner. Patients with HHT can develop vascular dysplasias called telangiectasias and arteriovenous malformations (AVMs). Our objective was to profile and characterize micro-RNAs (miRNAs), short noncoding RNAs that regulate gene expression posttranscriptionally, in HHT patient-derived peripheral blood mononuclear cells (PBMCs). PBMCs, comprised mostly of lymphocytes and monocytes, have been reported to be dysfunctional in HHT. A total of 40 clinically confirmed HHT patients and 22 controls were enrolled in this study. PBMCs were isolated from 16 mL of peripheral blood and purified for total RNA. MiRNA expression profiling was conducted with a human miRNA array analysis. Select dysregulated miRNAs and miRNA targets were validated with reverse transcription–quantitative polymerase chain reaction. Of the 377 miRNAs screened, 41 dysregulated miRNAs were identified. Both miR-28-5p and miR-361-3p, known to target insulin-like growth factor 1 (IGF1), a potent angiogenic growth factor, were found to be significantly downregulated in HHT patients. Consequently, IGF1 mRNA levels were found to be significantly elevated. Our research successfully identified miRNA dysregulation and elevated IGF1 mRNA levels in PBMCs from HHT patients. This novel discovery represents a potential pathogenic mechanism that could be targeted to alleviate clinical manifestations of HHT.
Singularities of worldsheets associated with null Cartan curves in Lorentz–Minkowski space–time
Authors: Liu Siyao , Wang Zhigang
Published: December 2018

In this paper, as applications of singularity theory, we study the singularities of several worldsheets generated by null Cartan curves in Lorentz–Minkowski space–time. Using the approach of the unfolding theory in singularity theory, we establish the relationships between these worldsheets and invariants such that the cuspidal edge type of singularity and the swallowtail type of singularity can be characterized by these invariants, respectively. Meanwhile, the contact of the tangent curve of a null Cartan curve with some model surfaces are discussed in detail. In addition, we also describe the dual relationships between the tangent curve of a null Cartan curve and these worldsheets. Finally, some concrete examples are provided to explain our theoretical results.
Description of ϕ-meson production in hadronic and nuclear collisions at very high energies
Authors: Arakelyan G. H. , Merino C. , Shabelski Yu. M.
Published: December 2018

We expose the current experimental and theoretical situation of the interesting case of the production of [Formula: see text] mesons in up to very high energy collisions of hadrons on both nucleon and nuclear targets, and we present a quantitatively good theoretical description of the corresponding experimental data, based on the formalism of the well established Quark–Gluon String Model, that has proved to be valid for a wide energy range. All the available experimental data for [Formula: see text]-meson production in hadron–nucleon collisions on the spectra of secondary [Formula: see text], and on the ratios of [Formula: see text] and [Formula: see text] production cross-sections, as well the corresponding ones for [Formula: see text]-meson production on nuclear targets, are considered. In particular, it is seen that the production of [Formula: see text]-mesons on nuclear targets presents unusually small shadow corrections for the inclusive density in the central rapidity region.
Characterization analysis and gate driver design for 1200 V 10 A SiC MOSFET
Authors: Zhai Mingjing , Yang Yuan , Wen Yang , Yao Wenqing , Li Yuan
Published: December 2018

Silicon carbide (SiC) metal-oxide-semiconductor field-effect transistor (MOSFET) can work at high switching frequency with low switching loss compared with Si insulated gate bipolar transistor (IGBT). Although Si IGBT and SiC MOSFET have the same MOS-gate structure, the transient characteristics and the gate driver requirements for Si IGBT and SiC MOSFET are different. In order to fully utilize the advantages of SiC MOSFET, the gate driver of SiC MOSFET needs to be optimized to meet some special driving requirements. The paper aims to analyze the characteristics for the new generation of wide band gap semiconductor device SiC MOSFET and proposes a novel gate driver for SiC MOSFET. Meanwhile, the driving protection circuit of SiC MOSFET is also investigated. The performances of the proposed gate driver have been experimentally evaluated by double pulse test (DPT). In addition, the effect of different external capacitors [Formula: see text] and external driving resistances [Formula: see text] on the switch characteristics of SiC MOSFET is analyzed in detail.
Fractal simulation of thin film nucleation growth process using a diffusion-limited aggregation model
Authors: Zhang Min , Deng Chaoyong
Published: December 2018

In order to study the initial nucleation and growth process of the films, a two-dimensional (2D) DLA model was established, and fractal dimension was calculated by sandbox method. Compared with the experimental results, the model can well characterize the morphology of nucleation and growth in the initial stage of film growth. In addition to the number of particles and deposition probability involved in other studies, the size of substrate and the location of central particles are also considered in this work. The growth morphology, fractal dimension and the number of simulated steps are presented in this paper.
Frequency-dependent dielectric properties of sodium silicate
Authors: Chakraborty Sudhangshu
Published: December 2018

The dielectric properties of sodium silicate (Na2SiO3) (SS) have been investigated in a wide range of frequencies and temperatures. A strong dielectric dispersion is found to exist in low-frequency region. The frequency-dependent dielectric properties of SS follow the universal dynamic response proposed by Jonscher. The measured dielectric data strongly depends on dielectric dispersion and controls the basic relaxation property. However, the parameters that control the frequency-dependent dielectric properties such as coupling of ions or polarizability are found to have peak values at the frozen out condition or critical point.
An Autonomic Cognitive Pattern for Smart IoT-Based System Manageability
Authors: Mezghani Emna , Exposito Ernesto , Drira Khalil
Published: December 2018

The adoption of the Internet of Things (IoT) drastically witnesses an increase in different domains and contributes to the fast digitalization of the universe. Henceforth, next generation of IoT-based systems are set to become more complex to design and manage. Collecting real-time IoT-generated data unleashes a new wave of opportunities for business to take more precise and accurate decisions at the right time. However, a set of challenges, including the design complexity of IoT-based systems and the management of the ensuing heterogeneous big data as well as the system scalability, need to be addressed for the development of flexible smart IoT-based systems. Consequently, we proposed a set of design patterns that diminish the system design complexity through selecting the appropriate combination of patterns based on the system requirements. These patterns identify four maturity levels for the design and development of smart IoT-based systems. In this article, we are mainly dealing with the system design complexity to manage the context changeability at runtime. Thus, we delineate the autonomic cognitive management pattern, which is at the most mature level. Based on the autonomic computing, this pattern identifies a combination of management processes able to continuously detect and manage the context changes. These processes are coordinated based on cognitive mechanisms that allow the system perceiving and understanding the meaning of the received data to make business decisions, as well as dynamically discovering new processes that meet the requirements evolution at runtime. We demonstrated the use of the proposed pattern with a use case from the healthcare domain; more precisely, the patient comorbidity management based on wearables.
New Phone, Who Dis? Modeling Millennials’ Backup Behavior
Authors: Redmiles Elissa M. , Hargittai Eszter
Published: December 2018

Given the ever-rising frequency of malware attacks and other problems leading people to lose their files, backups are an important proactive protective behavior in which users can engage. Backing up files can prevent emotional and financial losses and improve overall user experience. Yet, we find that less than half of young adults perform mobile or computer backups regularly. To understand why, we model the factors that drive mobile and computer backup behavior, and changes in that behavior over time, using data from a panel survey of 384 diverse young adults. We develop a set of models that explain 37% and 38% of the variance in reported mobile and computer backup behaviors, respectively. These models show consistent relationships between Internet skills and backup frequency on both mobile and computer devices. We find that this relationship holds longitudinally: increases in Internet skills lead to increased frequency of computer backups. This article provides a foundation for understanding what drives young adults’ backup behavior. It concludes with recommendations for motivating people to back up, and for future work, modeling similar user behaviors.
Performance Characterization of NVMe-over-Fabrics Storage Disaggregation
Authors: Guz Zvika , Li Harry (Huan) , Shayesteh Anahita , Balakrishnan Vijay
Published: December 2018

Storage disaggregation separates compute and storage to different nodes to allow for independent resource scaling and, thus, better hardware resource utilization. While disaggregation of hard-drives storage is a common practice, NVMe-SSD (i.e., PCIe-based SSD) disaggregation is considered more challenging. This is because SSDs are significantly faster than hard drives, so the latency overheads (due to both network and CPU processing) as well as the extra compute cycles needed for the offloading stack become much more pronounced.

In this work, we characterize the overheads of NVMe-SSD disaggregation. We show that NVMe-over-Fabrics (NVMe-oF)—a recently released remote storage protocol specification—reduces the overheads of remote access to a bare minimum, thus greatly increasing the cost-efficiency of Flash disaggregation. Specifically, while recent work showed that SSD storage disaggregation via iSCSI degrades application-level throughput by 20%, we report on negligible performance degradation with NVMe-oF—both when using stress-tests as well as with a more-realistic KV-store workload.
Liquid Silicon-Monona
Authors: Zha Yue , Li Jing
Published: December 2018

With the recent trend of promoting Field-Programmable Gate Arrays (FPGAs) to first-class citizens in accelerating compute-intensive applications in networking, cloud services and artificial intelligence, FPGAs face two major challenges in sustaining competitive advantages in performance and energy efficiency for diverse cloud workloads: 1) limited configuration capability for supporting light-weight computations/on-chip data storage to accelerate emerging search-/data-intensive applications. 2) lack of architectural support to hide reconfiguration overhead for assisting virtualization in a cloud computing environment. In this paper, we propose a reconfigurable memory-oriented computing fabric, namely Liquid Silicon-Monona (L-Si), enabled by emerging nonvolatile memory technology i.e. RRAM, to address these two challenges. Specifically, L-Si addresses the first challenge by virtue of a new architecture comprising a 2D array of physically identical but functionally-configurable building blocks. It, for the first time, extends the configuration capabilities of existing FPGAs from computation to the whole spectrum ranging from computation to data storage. It allows users to better customize hardware by flexibly partitioning hardware resources between computation and memory, greatly benefiting emerging search- and data-intensive applications. To address the second challenge, L-Si provides scalable multi-context architectural support to minimize reconfiguration overhead for assisting virtualization. In addition, we provide compiler support to facilitate the programming of applications written in high-level programming languages (e.g. OpenCL) and frameworks (e.g. TensorFlow, MapReduce) while fully exploiting the unique architectural capability of L-Si. Our evaluation results show L-Si achieves 99.6% area reduction, 1.43× throughput improvement and 94.0% power reduction on search-intensive benchmarks, as compared with the FPGA baseline. For neural network benchmarks, on average, L-Si achieves 52.3× speedup, 113.9× energy reduction and 81% area reduction over the FPGA baseline. In addition, the multi-context architecture of L-Si reduces the context switching time to - 10ns, compared with an off-the-shelf FPGA (∼100ms), greatly facilitating virtualization.
Automatic Hierarchical Parallelization of Linear Recurrences
Authors: Maleki Sepideh , Burtscher Martin
Published: December 2018

Linear recurrences encompass many fundamental computations including prefix sums and digital filters. Later result values depend on earlier result values in recurrences, making it a challenge to compute them in parallel. We present a new work- and space-efficient algorithm to compute linear recurrences that is amenable to automatic parallelization and suitable for hierarchical massively-parallel architectures such as GPUs. We implemented our approach in a domain-specific code generator that emits optimized CUDA code. Our evaluation shows that, for standard prefix sums and single-stage IIR filters, the generated code reaches the throughput of memory copy for large inputs, which cannot be surpassed. On higher-order prefix sums, it performs nearly as well as the fastest handwritten code from the literature. On tuple-based prefix sums and digital filters, our automatically parallelized code outperforms the fastest prior implementations.
Automatic Matching of Legacy Code to Heterogeneous APIs
Authors: Ginsbach Philip , Remmelg Toomas , Steuwer Michel , Bodin Bruno , Dubach Christophe , O'Boyle Michael F. P.
Published: December 2018

Heterogeneous accelerators often disappoint. They provide the prospect of great performance, but only deliver it when using vendor specific optimized libraries or domain specific languages. This requires considerable legacy code modifications, hindering the adoption of heterogeneous computing. This paper develops a novel approach to automatically detect opportunities for accelerator exploitation. We focus on calculations that are well supported by established APIs: sparse and dense linear algebra, stencil codes and generalized reductions and histograms. We call them idioms and use a custom constraint-based Idiom Description Language (IDL) to discover them within user code. Detected idioms are then mapped to BLAS libraries, cuSPARSE and clSPARSE and two DSLs: Halide and Lift. We implemented the approach in LLVM and evaluated it on the NAS and Parboil sequential C/C++ benchmarks, where we detect 60 idiom instances. In those cases where idioms are a significant part of the sequential execution time, we generate code that achieves 1.26x to over 20x speedup on integrated and external GPUs.
The Architectural Implications of Autonomous Driving
Authors: Lin Shih-Chieh , Zhang Yunqi , Hsu Chang-Hong , Skach Matt , Haque Md E. , Tang Lingjia , Mars Jason
Published: December 2018

Autonomous driving systems have attracted a significant amount of interest recently, and many industry leaders, such as Google, Uber, Tesla, and Mobileye, have invested a large amount of capital and engineering power on developing such systems. Building autonomous driving systems is particularly challenging due to stringent performance requirements in terms of both making the safe operational decisions and finishing processing at real-time. Despite the recent advancements in technology, such systems are still largely under experimentation and architecting end-to-end autonomous driving systems remains an open research question. To investigate this question, we first present and formalize the design constraints for building an autonomous driving system in terms of performance, predictability, storage, thermal and power. We then build an end-to-end autonomous driving system using state-of-the-art award-winning algorithms to understand the design trade-offs for building such systems. In our real-system characterization, we identify three computational bottlenecks, which conventional multicore CPUs are incapable of processing under the identified design constraints. To meet these constraints, we accelerate these algorithms using three accelerator platforms including GPUs, FPGAs, and ASICs, which can reduce the tail latency of the system by 169x, 10x, and 93x respectively. With accelerator-based designs, we are able to build an end-to-end autonomous driving system that meets all the design constraints, and explore the trade-offs among performance, power and the higher accuracy enabled by higher resolution cameras.
SOFRITAS
Authors: DeLozier Christian , Eizenberg Ariel , Lucia Brandon , Devietti Joseph
Published: December 2018

Correctly synchronizing multithreaded programs is challenging and errors can lead to program failures such as atomicity violations. Existing strong memory consistency models rule out some possible failures, but are limited by depending on programmer-defined locking code. We present the new Ordering-Free Region (OFR) serializability consistency model that ensures atomicity for OFRs, which are spans of dynamic instructions between consecutive ordering constructs (e.g., barriers), without breaking atomicity at lock operations. Our platform, Serializable Ordering-Free Regions for Increasing Thread Atomicity Scalably (SOFRITAS), ensures a C/C++ program's execution is equivalent to a serialization of OFRs by default. We build two systems that realize the SOFRITAS idea: a concurrency bug finding tool for testing called SOFRITEST, and a production runtime system called SOPRO. SOFRITEST uses OFRs to find concurrency bugs, including a multi-critical-section atomicity violation in memcached that weaker consistency models will miss. If OFR's are too coarse-grained, SOFRITEST suggests refinement annotations automatically. Our software-only SOPRO implementation has high performance, scales well with increased parallelism, and prevents failures despite bugs in locking code. SOFRITAS has an average overhead of just 1.59x on a single-threaded execution and 1.51x on sixteen threads, despite pthreads' much weaker memory model.
Making Huge Pages Actually Useful
Authors: Panwar Ashish , Prasad Aravinda , Gopinath K.
Published: December 2018

The virtual-to-physical address translation overhead, a major performance bottleneck for modern workloads, can be effectively alleviated with huge pages. However, since huge pages must be mapped contiguously, OSs have not been able to use them well because of the memory fragmentation problem despite hardware support for huge pages being available for nearly two decades. This paper presents a comprehensive study of the interaction of fragmentation with huge pages in the Linux kernel. We observe that when huge pages are used, problems such as high CPU utilization and latency spikes occur because of unnecessary work (e.g., useless page migration) performed by memory management related subsystems due to the poor handling of unmovable (i.e., kernel) pages. This behavior is even more harmful in virtualized systems where unnecessary work may be performed in both guest and host OSs. We present Illuminator, an efficient memory manager that provides various subsystems, such as the page allocator, the ability to track all unmovable pages. It allows subsystems to make informed decisions and eliminate unnecessary work which in turn leads to cost-effective huge page allocations. Illuminator reduces the cost of compaction (up to 99%), improves application performance (up to 2.3x) and reduces the maximum latency of MySQL database server (by 30x). Importantly, this work shows the effectiveness of a simple solution for long-standing huge page related problems.
Bridge the Gap between Neural Networks and Neuromorphic Hardware with a Neural Network Compiler
Authors: Ji Yu , Zhang Youhui , Chen Wenguang , Xie Yuan
Published: December 2018

Different from developing neural networks (NNs) for general-purpose processors, the development for NN chips usually faces with some hardware-specific restrictions, such as limited precision of network signals and parameters, constrained computation scale, and limited types of non-linear functions. This paper proposes a general methodology to address the challenges. We decouple the NN applications from the target hardware by introducing a compiler that can transform an existing trained, unrestricted NN into an equivalent network that meets the given hardware's constraints. We propose multiple techniques to make the transformation adaptable to different kinds of NN chips, and reliable for restrict hardware constraints. We have built such a software tool that supports both spiking neural networks (SNNs) and traditional artificial neural networks (ANNs). We have demonstrated its effectiveness with a fabricated neuromorphic chip and a processing-in-memory (PIM) design. Tests show that the inference error caused by this solution is insignificant and the transformation time is much shorter than the retraining time. Also, we have studied the parameter-sensitivity evaluations to explore the tradeoffs between network error and resource utilization for different transformation strategies, which could provide insights for co-design optimization of neuromorphic hardware and software.
FirmUp
Authors: David Yaniv , Partush Nimrod , Yahav Eran
Published: December 2018

We present a static, precise, and scalable technique for finding CVEs (Common Vulnerabilities and Exposures) in stripped firmware images. Our technique is able to efficiently find vulnerabilities in real-world firmware with high accuracy. Given a vulnerable procedure in an executable binary and a firmware image containing multiple stripped binaries, our goal is to detect possible occurrences of the vulnerable procedure in the firmware image. Due to the variety of architectures and unique tool chains used by vendors, as well as the highly customized nature of firmware, identifying procedures in stripped firmware is extremely challenging. Vulnerability detection requires not only pairwise similarity between procedures but also information about the relationships between procedures in the surrounding executable. This observation serves as the foundation for a novel technique that establishes a partial correspondence between procedures in the two binaries. We implemented our technique in a tool called FirmUp and performed an extensive evaluation over 40 million procedures, over 4 different prevalent architectures, crawled from public vendor firmware images. We discovered 373 vulnerabilities affecting publicly available firmware, 147 of them in the latest available firmware version for the device. A thorough comparison of FirmUp to previous methods shows that it accurately and effectively finds vulnerabilities in firmware, while outperforming the detection rate of the state of the art by 45% on average.
Enhancing Cross-ISA DBT Through Automatically Learned Translation Rules
Authors: Wang Wenwen , McCamant Stephen , Zhai Antonia , Yew Pen-Chung
Published: December 2018

This paper presents a novel approach for dynamic binary translation (DBT) to automatically learn translation rules from guest and host binaries compiled from the same source code. The learned translation rules are then verified via binary symbolic execution and used in an existing DBT system, QEMU, to generate more efficient host binary code. Experimental results on SPEC CINT2006 show that the average time of learning a translation rule is less than two seconds. With the rules learned from a collection of benchmark programs excluding the targeted program itself, an average 1.25X performance speedup over QEMU can be achieved for SPEC CINT2006. Moreover, the translation overhead introduced by this rule-based approach is very small even for short-running workloads.
VM Live Migration At Scale
Authors: Ruprecht Adam , Jones Danny , Shiraev Dmitry , Harmon Greg , Spivak Maya , Krebs Michael , Baker-Harvey Miche , Sanderson Tyler
Published: December 2018

Uninterrupted uptime is a critical aspect of Virtual Machines (VMs) offered by cloud hosting providers. Google's VMs run on top of rapidly changing infrastructure: we regularly update hardware and host software, and we must quickly respond to failing hardware. Frequent change is critical to both development velocity---deploying new versions of services and infrastructure---and the ability to respond rapidly to defects, including critical security fixes. Typically these updates would be disruptive, resulting in VM termination or restart. In this paper we present how we use VM live migration at scale to eliminate this disruption with minimal impact to the guest, performing over 1,000,0001migrations monthly in our production fleet, with 50ms median blackout, 300ms 99th percentile blackout.
Crellvm: verified credible compilation for LLVM
Authors: Kang Jeehoon , Kim Yoonseung , Song Youngju , Lee Juneyoung , Park Sanghoon , Shin Mark Dongyeon , Kim Yonghyun , Cho Sungkeun , Choi Joonwon , Hur Chung-Kil , Yi Kwangkeun
Published: December 2018

Production compilers such as GCC and LLVM are large complex software systems, for which achieving a high level of reliability is hard. Although testing is an effective method for finding bugs, it alone cannot guarantee a high level of reliability. To provide a higher level of reliability, many approaches that examine compilers' internal logics have been proposed. However, none of them have been successfully applied to major optimizations of production compilers.

This paper presents Crellvm: a verified credible compilation framework for LLVM, which can be used as a systematic way of providing a high level of reliability for major optimizations in LLVM. Specifically, we augment an LLVM optimizer to generate translation results together with their correctness proofs, which can then be checked by a proof checker formally verified in Coq. As case studies, we applied our approach to two major optimizations of LLVM: register promotion mem2reg and global value numbering gvn, having found four new miscompilation bugs (two in each).
Spatial: a language and compiler for application accelerators
Authors: Koeplinger David , Feldman Matthew , Prabhakar Raghu , Zhang Yaqi , Hadjis Stefan , Fiszel Ruben , Zhao Tian , Nardi Luigi , Pedram Ardavan , Kozyrakis Christos , Olukotun Kunle
Published: December 2018

Industry is increasingly turning to reconfigurable architectures like FPGAs and CGRAs for improved performance and energy efficiency. Unfortunately, adoption of these architectures has been limited by their programming models. HDLs lack abstractions for productivity and are difficult to target from higher level languages. HLS tools are more productive, but offer an ad-hoc mix of software and hardware abstractions which make performance optimizations difficult.

In this work, we describe a new domain-specific language and compiler called Spatial for higher level descriptions of application accelerators. We describe Spatial's hardware-centric abstractions for both programmer productivity and design performance, and summarize the compiler passes required to support these abstractions, including pipeline scheduling, automatic memory banking, and automated design tuning driven by active machine learning. We demonstrate the language's ability to target FPGAs and CGRAs from common source code. We show that applications written in Spatial are, on average, 42% shorter and achieve a mean speedup of 2.9x over SDAccel HLS when targeting a Xilinx UltraScale+ VU9P FPGA on an Amazon EC2 F1 instance.
Program synthesis using conflict-driven learning
Authors: Feng Yu , Martins Ruben , Bastani Osbert , Dillig Isil
Published: December 2018

We propose a new conflict-driven program synthesis technique that is capable of learning from past mistakes. Given a spurious program that violates the desired specification, our synthesis algorithm identifies the root cause of the conflict and learns new lemmas that can prevent similar mistakes in the future. Specifically, we introduce the notion of equivalence modulo conflict and show how this idea can be used to learn useful lemmas that allow the synthesizer to prune large parts of the search space. We have implemented a general-purpose CDCL-style program synthesizer called Neo and evaluate it in two different application domains, namely data wrangling in R and functional programming over lists. Our experiments demonstrate the substantial benefits of conflict-driven learning and show that Neo outperforms two state-of-the-art synthesis tools, Morpheus and Deepcoder, that target these respective domains.
Active learning of points-to specifications
Authors: Bastani Osbert , Sharma Rahul , Aiken Alex , Liang Percy
Published: December 2018

When analyzing programs, large libraries pose significant challenges to static points-to analysis. A popular solution is to have a human analyst provide points-to specifications that summarize relevant behaviors of library code, which can substantially improve precision and handle missing code such as native code. We propose Atlas, a tool that automatically infers points-to specifications. Atlas synthesizes unit tests that exercise the library code, and then infers points-to specifications based on observations from these executions. Atlas automatically infers specifications for the Java standard library, and produces better results for a client static information flow analysis on a benchmark of 46 Android apps compared to using existing handwritten specifications.
High-coverage, unbounded sound predictive race detection
Authors: Roemer Jake , Genç Kaan , Bond Michael D.
Published: December 2018

Dynamic program analysis can predict data races knowable from an observed execution, but existing predictive analyses either miss races or cannot analyze full program executions. This paper presents Vindicator, a novel, sound (no false races) predictive approach that finds more data races than existing predictive approaches. Vindicator achieves high coverage by using a new, efficient analysis that finds all possible predictable races but may detect false races. Vindicator ensures soundness using a novel algorithm that checks each potential race to determine whether it is a true predictable race. An evaluation using large Java programs shows that Vindicator finds hard-to-detect predictable races that existing sound predictive analyses miss, at a comparable performance cost.
EffectiveSan: type and memory error detection using dynamically typed C/C++
Authors: Duck Gregory J. , Yap Roland H. C.
Published: December 2018

Low-level programming languages with weak/static type systems, such as C and C++, are vulnerable to errors relating to the misuse of memory at runtime, such as (sub-)object bounds overflows, (re)use-after-free, and type confusion. Such errors account for many security and other undefined behavior bugs for programs written in these languages. In this paper, we introduce the notion of dynamically typed C/C++, which aims to detect such errors by dynamically checking the "effective type" of each object before use at runtime. We also present an implementation of dynamically typed C/C++ in the form of the Effective Type Sanitizer (EffectiveSan). EffectiveSan enforces type and memory safety using a combination of low-fat pointers, type meta data and type/bounds check instrumentation. We evaluate EffectiveSan against the SPEC2006 benchmark suite and the Firefox web browser, and detect several new type and memory errors. We also show that EffectiveSan achieves high compatibility and reasonable overheads for the given error coverage. Finally, we highlight that EffectiveSan is one of only a few tools that can detect sub-object bounds errors, and uses a novel approach (dynamic type checking) to do so.