bluuebunny/crossref_metadata_2025 huggingface dataset:
Fucoidan reduces inflammatory response in a rat model of hepatic ischemia–reperfusion injury
Authors: Li Xiao-jing , Ye Qi-fa
Published: June 2015

Ischemia–reperfusion (I/R) injury after a liver transplant is a major cause of severe complications that lead to graft dysfunction. Fucoidan, a complex of sulfated polysaccharides derived from marine brown algae, demonstrated antiapoptotic as well as potential anti-inflammatory properties in previous studies. Fucoidan has also shown protective effects on I/R-injured kidney and heart. However, whether fucoidan can attenuate hepatic I/R injury has not been examined. To clarify the role of fucoidan in hepatic I/R injury, Sprague–Dawley rats were subjected to sham operation or ischemia followed by reperfusion with treatment of saline or fucoidan (50, 100, or 200 mg·(kg body mass)−1·d−1). The fucoidan-treated group showed decreased levels of alanine aminotransferase and aspartate aminotransferase compared with the control group. Myeloperoxidase and malondialdehyde activities and mRNA levels of CD11b in the fucoidan-treated group were significantly decreased. Hepatocellular swelling/necrosis, sinusoidal/vascular congestion, and inflammatory cell infiltration were also attenuated in the fucoidan group. The expression of TNF-α, IL-6, IL-1β, CXCL-10, VCAM-1, and ICAM-1 were markedly decreased in the samples from the fucoidan-treated group. Fucoidan largely prevented activation of the inflammatory signaling pathway, compared with the control group. In summary, fucoidan can protect the liver from I/R injury through suppressing activation of the inflammatory signaling pathway, as well as the expression of inflammatory mediators, and inflammatory cell infiltration.
QED representation for the net of causal loops
Authors: Ciolli Fabio , Ruzzi Giuseppe , Vasselli Ezio
Published: June 2015

The present work tackles the existence of local gauge symmetries in the setting of Algebraic Quantum Field Theory (AQFT). The net of causal loops, previously introduced by the authors, is a model independent construction of a covariant net of local C*-algebras on any 4-dimensional globally hyperbolic space-time, aimed to capture structural properties of any reasonable quantum gauge theory. Representations of this net can be described by causal and covariant connection systems, and local gauge transformations arise as maps between equivalent connection systems. The present paper completes these abstract results, realizing QED as a representation of the net of causal loops in Minkowski space-time. More precisely, we map the quantum electromagnetic field Fμν, not free in general, into a representation of the net of causal loops and show that the corresponding connection system and the local gauge transformations find a counterpart in terms of Fμν.
A Hybrid Approach for Person Identification Using Palmprint and Face Biometrics
Authors: Farmanbar Mina , Toygar Önsen
Published: June 2015

This paper proposes hybrid approaches based on both feature level and score level fusion strategies to provide a robust recognition system against the distortions of individual modalities. In order to compare the proposed schemes, a virtual multimodal database is formed from FERET face and PolyU palmprint databases. The proposed hybrid systems concatenate features extracted by local and global feature extraction methods such as Local Binary Patterns, Log Gabor, Principal Component Analysis and Linear Discriminant Analysis. Match score level fusion is performed in order to show the effectiveness and accuracy of the proposed schemes. The experimental results based on these databases reported a significant improvement of the proposed schemes compared with unimodal systems and other multimodal face–palmprint fusion methods.
A Multi-Stage Krill Herd Algorithm for Global Numerical Optimization
Authors: Wang Gai-Ge , Gandomi Amir H. , Alavi Amir H. , Deb Suash
Published: June 2015

A multi-stage krill herd (MSKH) algorithm is presented to fully exploit the global and local search abilities of the standard krill herd (KH) optimization method. The proposed method involves exploration and exploitation stages. The exploration stage uses the basic KH algorithm to select a good candidate solution set. This phase is followed by fine-tuning a good candidate solution in the exploitation stage with a focused local mutation and crossover (LMC) operator in order to enhance the reliability of the method for solving global numerical optimization problems. Moreover, the elitism scheme is introduced into the MSKH method to guarantee the best solution. The performance of MSKH is verified using twenty-five standard and rotated and shifted benchmark problems. The results show the superiority of the proposed algorithm to the standard KH and other well-known optimization methods.
Hierarchical model of the actomyosin molecular motor based on ultrametric diffusion with drift
Authors: Khrennikov Andrei , Kozyrev Sergei , Månsson Alf
Published: June 2015

We discuss the approach to investigate molecular machines using systems of integro–differential ultrametric (p-adic) reaction–diffusion equations with drift. This approach combines the features of continuous and discrete dynamic models. We apply this model to investigation of actomyosin molecular motor.

The introduced system of equations is solved analytically using p-adic wavelet theory. We find explicit stationary solutions and behavior in the relaxation regime.
On Bargaining Sets of Convex NTU Games
Authors: Peleg Bezalel , Sudhölter Peter
Published: June 2015

We show that the Aumann–Davis–Maschler bargaining set and the Mas-Colell bargaining set of a non-leveled NTU game that is either ordinal convex or coalition merge convex coincides with the core of the game. Moreover, we show by means of an example that the foregoing statement may not be valid if the NTU game is marginal convex.
A new approach to Poincaré-type inequalities on the Wiener space
Authors: Lanconelli Alberto
Published: June 2015

We prove a new type of Poincaré inequality on abstract Wiener spaces for a family of probability measures that are absolutely continuous with respect to the reference Gaussian measure. This class of probability measures is characterized by the strong positivity (a notion introduced by Nualart and Zakai in [22]) of their Radon–Nikodym densities. In general, measures of this type do not belong to the class of log-concave measures, which are a wide class of measures satisfying the Poincaré inequality (Brascamp and Lieb [2]). Our approach is based on a pointwise identity relating Wick and ordinary products and on the notion of strong positivity which is connected to the non-negativity of Wick powers. Our technique also leads to a partial generalization of the Houdré and Kagan [11] and Houdré and Pérez-Abreu [12] Poincaré-type inequalities.
The Process of Entrepreneurial Revolution: Case Study of the National Research University of Thailand
Authors: Wonglimpiyarat Jarunee
Published: June 2015

This paper discusses the process of entrepreneurial revolution at Mahidol University, Thailand. The aim of this study is to understand the process of technology transfer and commercialization of Mahidol University, one of the national research universities and the most leading university business incubator (UBI) in Thailand. The case study explores the process of implementing the national technology transfer strategy to become an entrepreneurial university. The discussions include the policy of UBIs to support transfer of university innovations. The empirical study provides insightful implications on the process of revolution and the capacity of university technology transfer and commercialization.
Black ring and Kerr ellipsoid — Solitonic configurations in modified Finsler gravity
Authors: Rajpoot Subhash , Vacaru Sergiu I.
Published: June 2015

We study an effective Einstein–Finsler theory on tangent Lorentz bundle constructed as a "minimal" extension of general relativity. Black ring and Kerr-like ellipsoid exact solutions and solitonic configurations are presented. In this endeavor the relevant metric depends not only on four-dimensional spacetime coordinates and also on velocity type variables that can be interpreted as additional coordinates in the space of "extra dimensions".
A facile synthetic route to meso-tetraaryl substituted N-5 sapphyrins and first single crystal X-ray analysis confirming the pyrrole inverted structure
Authors: Huang Wenhao , Ou Zhongping , Chen Xueyan , Xue Zhaoli , Lu Guifen , Wang Hui , Xiao Jingjing , Fang Yuanyuan , Kadish Karl M.
Published: June 2015

Three meso-tetraaryl substituted N -5 sapphyrins were synthesized by a facile synthetic route from the corresponding open-chain pentapyrroles in high yield using acetic acid as the solvent and catalyst. Each compound was characterized by spectroscopic and electrochemical methods and the inverted pyrrole structure was confirmed in the solid state for the first time by single crystal X-ray analysis.
Functionalization of graphene with hyperbranched polyglycerol for stable aqueous dispersion
Authors: Cai Ning , Hou Dajun , Shen Liang , Luo Xiaogang , Xue Yanan , Yu Faquan
Published: June 2015

The application of graphene for some particular fields including biomedical engineering was hindered by its poor aqueous dispersivity and hydrophobic property. In this study, the strategy of the functionalization of graphene with hyperbranched polyglycerol (HPG) by a facile procedure was proposed. By the epoxy ring-opening hyperbranched polymerization of glycidol, graphene surface was grafted with HPG layer with rich hydroxyl groups. The content of polyglycerol on HPG functionalized graphene (HPG-G) was determined to be 55%. The results of fourier transform infrared (FTIR), X-ray diffraction (XRD), Raman, X-ray photoelectron spectroscopy (XPS) and UV–Vis demonstrated that HPG was successfully grafted onto graphene sheets (GSs), and the aromatic and crystalline structure of graphene was maintained after HPG functionalization. The obtained HPG-G composites possess high hydrophilicity and can be dispersed well in water. Furthermore, no discernable precipitation was found in HPG-G aqueous solution even after three months of storage.
Review on the Latest Conclusions of Working Group III Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change
Authors: FU Sha , ZOU Ji , ZHANG Xiaohua , QI Yue
Published: June 2015

Intergovernmental Panel on Climate Change (IPCC) issued its latest research Working Group III Contribution to the Fifth Assessment Report (WGIII AR5) on April 2014. This report is designated to provide approaches to limit temperature rise below 2°C based upon reviews of latest literatures in this terrain. It offers comprehensive review on principles and conceptual frameworks of climate change mitigation, trends in stocks and flows of greenhouse gases and their drivers, mitigation targets and pathways, sectoral reduction potential and costs, international institutions on climate change mitigation, national and sub-national policies, climate finance, and other related issues. The report, contributed by WGIII, systematically analyzes these questions and assesses principals, framework problems, historic trajectories, future emission budgets and pathways, sectoral reduction targets and feasibilities, and national, sub-national, and international policies, and finance demands upon which to achieve the target to limit temperature rise within 2°C. These contents make the report a critical venue of international society to vie for political influences through social sciences, natural sciences, and other disciplines. This paper provides preliminary analysis upon main conclusions of the report and their policy interpretations, in order to deliver better technical support for climate negotiations in next stage and advancing relevant domestic works.
Remark on Algorithm 897
Authors: Sosonkina Masha , Watson Layne T. , He Jian
Published: June 2015

The Fortran95 code VTDIRECT95, based on the original MPI, has been modified to use MPI-2. An option for VTDIRECT95 is to divide the feasible box into subdomains, and concurrently apply the global direct search algorithm DIRECT within each subdomain. When the number of subdomains is greater than one, a bug causes VTDIRECT95 to occasionally sample outside the given feasible box, which is serious if the objective function is not defined outside the given box. This bug has been fixed, and the sample output files have been updated to reflect the correction. For completeness, the package VTDIRECT95 now contains both the MPI-1 (with the multiple subdomain bug fixed) and the MPI-2 versions of the code.
Optimizing Text Quantifiers for Multivariate Loss Functions
Authors: Esuli Andrea , Sebastiani Fabrizio
Published: June 2015

We address the problem of
quantification
, a supervised learning task whose goal is, given a class, to estimate the relative frequency (or
prevalence
) of the class in a dataset of unlabeled items. Quantification has several applications in data and text mining, such as estimating the prevalence of positive reviews in a set of reviews of a given product or estimating the prevalence of a given support issue in a dataset of transcripts of phone calls to tech support. So far, quantification has been addressed by learning a general-purpose classifier, counting the unlabeled items that have been assigned the class, and tuning the obtained counts according to some heuristics. In this article, we depart from the tradition of using general-purpose classifiers and use instead a supervised learning model for
structured prediction
, capable of generating classifiers directly optimized for the (multivariate and nonlinear) function used for evaluating quantification accuracy. The experiments that we have run on 5,500 binary high-dimensional datasets (averaging more than 14,000 documents each) show that this method is more accurate, more stable, and more efficient than existing state-of-the-art quantification methods.
Classification with Streaming Features: An Emerging-Pattern Mining Approach
Authors: Yu Kui , Ding Wei , Simovici Dan A. , Wang Hao , Pei Jian , Wu Xindong
Published: June 2015

Many datasets from real-world applications have very high-dimensional or increasing feature space. It is a new research problem to learn and maintain a classifier to deal with very high dimensionality or streaming features. In this article, we adapt the well-known emerging-pattern--based classification models and propose a semi-streaming approach. For streaming features, it is computationally expensive or even prohibitive to mine long-emerging patterns, and it is nontrivial to integrate emerging-pattern mining with feature selection. We present an online feature selection step, which is capable of selecting and maintaining a pool of effective features from a feature stream. Then, in our offline step, separated from the online step, we periodically compute and update emerging patterns from the pool of selected features from the online step. We evaluate the effectiveness and efficiency of the proposed method using a series of benchmark datasets and a real-world case study on Mars crater detection. Our proposed method yields classification performance comparable to the state-of-art static classification methods. Most important, the proposed method is significantly faster and can efficiently handle datasets with streaming features.
Supporting Exploratory Hypothesis Testing and Analysis
Authors: Liu Guimei , Zhang Haojun , Feng Mengling , Wong Limsoon , Ng See-Kiong
Published: June 2015

Conventional hypothesis testing is carried out in a hypothesis-driven manner. A scientist must first formulate a hypothesis based on what he or she sees and then devise a variety of experiments to test it. Given the rapid growth of data, it has become virtually impossible for a person to manually inspect all data to find all of the interesting hypotheses for testing. In this article, we propose and develop a data-driven framework for automatic hypothesis testing and analysis. We define a hypothesis as a comparison between two or more subpopulations. We find subpopulations for comparison using frequent pattern mining techniques and then pair them up for statistical hypothesis testing. We also generate additional information for further analysis of the hypotheses that are deemed significant. The number of hypotheses generated can be very large, and many of them are very similar. We develop algorithms to remove redundant hypotheses and present a succinct set of significant hypotheses to users. We conducted a set of experiments to show the efficiency and effectiveness of the proposed algorithms. The results show that our system can help users (1) identify significant hypotheses efficiently, (2) isolate the reasons behind significant hypotheses efficiently, and (3) find confounding factors that form Simpson’s paradoxes with discovered significant hypotheses.
Cache-Centric Video Recommendation
Authors: Krishnappa Dilip Kumar , Zink Michael , Griwodz Carsten , Halvorsen Pål
Published: June 2015

In this article, we take advantage of the user behavior of requesting videos from the top of the related list provided by YouTube to improve the performance of YouTube caches. We recommend that local caches reorder the related lists associated with YouTube videos, presenting the cached content above noncached content. We argue that the likelihood that viewers select content from the top of the related list is higher than selection from the bottom, and pushing contents already in the cache to the top of the related list would increase the likelihood of choosing cached content. To verify that the position on the list really is the selection criterion more dominant than the content itself, we conduct a user study with 40 YouTube-using volunteers who were presented with random related lists in their everyday YouTube use. After confirming our assumption, we analyze the benefits of our approach by an investigation that is based on two traces collected from a university campus. Our analysis shows that the proposed reordering approach for related lists would lead to a 2 to 5 times increase in cache hit rate compared to an approach without reordering the related list. This increase in hit rate would lead to reduction in server load and backend bandwidth usage, which in turn reduces the latency in streaming the video requested by the viewer and has the potential to improve the overall performance of YouTube's content distribution system. An analysis of YouTube's recommendation system reveals that related lists are created from a small pool of videos, which increases the potential for caching content from related lists and reordering based on the content in the cache.
Understanding Business Ecosystem Dynamics
Authors: Basole Rahul C. , Russell Martha G. , Huhtamäki Jukka , Rubens Neil , Still Kaisa , Park Hyunwoo
Published: June 2015

Business ecosystems consist of a heterogeneous and continuously evolving set of entities that are interconnected through a complex, global network of relationships. However, there is no well-established methodology to study the dynamics of this network. Traditional approaches have primarily utilized a single source of data of relatively established firms; however, these approaches ignore the vast number of relevant activities that often occur at the individual and entrepreneurial levels. We argue that a data-driven visualization approach, using both institutionally and socially curated datasets, can provide important complementary, triangulated explanatory insights into the dynamics of interorganizational networks in general and business ecosystems in particular. We develop novel visualization layouts to help decision makers systemically identify and compare ecosystems. Using traditionally disconnected data sources on deals and alliance relationships (DARs), executive and funding relationships (EFRs), and public opinion and discourse (POD), we empirically illustrate our data-driven method of data triangulation and visualization techniques through three cases in the mobile industry Google’s acquisition of Motorola Mobility, the coopetitive relation between Apple and Samsung, and the strategic partnership between Nokia and Microsoft. The article concludes with implications and future research opportunities.
An Advanced Visibility Restoration Algorithm for Single Hazy Images
Authors: Chen Bo-Hao , Huang Shih-Chia
Published: June 2015

Haze removal is the process by which horizontal obscuration is eliminated from hazy images captured during inclement weather. Images captured in natural environments with varied weather conditions frequently exhibit localized light sources or color-shift effects. The occurrence of these effects presents a difficult challenge for hazy image restoration, with which many traditional restoration methods cannot adequately contend. In this article, we present a new image haze removal approach based on Fisher's linear discriminant-based dual dark channel prior scheme in order to solve the problems associated with the presence of localized light sources and color shifts, and thereby achieve effective restoration. Experimental restoration results via qualitative and quantitative evaluations show that our proposed approach can provide higher haze-removal efficacy for images captured in varied weather conditions than can the other state-of-the-art approaches.
Nonelementary Complexities for Branching VASS, MELL, and Extensions
Authors: Lazić Ranko , Schmitz Sylvain
Published: June 2015

We study the complexity of reachability problems on branching extensions of vector addition systems, which allows us to derive new non-elementary complexity bounds for fragments and variants of propositional linear logic. We show that provability in the multiplicative exponential fragment is T
ower
-hard already in the affine case—and hence non-elementary. We match this lower bound for the full propositional affine linear logic, proving its T
ower
-completeness. We also show that provability in propositional contractive linear logic is A
ckermann
-complete.
A SAT Approach to Clique-Width
Authors: Heule Marijn J. H. , Szeider Stefan
Published: June 2015

Clique-width is a graph invariant that has been widely studied in combinatorics and computational logic. Computing the clique-width of a graph is an intricate problem, because the exact clique-width is not known even for very small graphs. We present a new method for computing clique-width via an encoding to propositional satisfiability (SAT), which is then evaluated by a SAT solver. Our encoding is based on a reformulation of clique-width in terms of partitions that utilizes an efficient encoding of cardinality constraints. Our SAT-based method is the first to discover the exact clique-width of various small graphs, including famous named graphs from the literature as well as random graphs of various density. With our method, we determined the smallest graphs that require a small predescribed clique-width. We further show how our method can be modified to compute the linear clique-width of graphs, a variant of clique-width that has recently received considerable attention. In an appendix, we provide certificates for tight upper bounds for the clique-width and linear clique-width of famous named graphs.
Replicated Computational Results (RCR) Report for “BLIS: A Framework for Rapidly Instantiating BLAS Functionality”
Authors: Willenbring James M.
Published: June 2015

“BLIS: A Framework for Rapidly Instantiating BLAS Functionality” by Field G. Van Zee and Robert A. van de Geijn (see:
http://dx.doi.org/10.1145/2764454
) includes single-platform BLIS performance results for both level-2 and level-3 operations that is competitive with OpenBLAS, ATLAS, and Intel MKL. A detailed description of the configuration used to generate the performance results was provided to the reviewer by the authors. All the software components used in the comparison were reinstalled and new performance results were generated and compared to the original results. After completing this process, the published results are deemed replicable by the reviewer.
Efficient MAC for Real-Time Video Streaming over Wireless LAN
Authors: Baik Eilwoo , Pande Amit , Mohapatra Prasant
Published: June 2015

Wireless communication systems are highly prone to channel errors. With video being a major player in Internet traffic and undergoing exponential growth in wireless domain, we argue for the need of a Video-aware MAC (VMAC) to significantly improve the throughput and delay performance of real-time video streaming service. VMAC makes two changes to optimize wireless LAN for video traffic: (a) It incorporates a Perceptual-Error-Tolerance (PET) to the MAC frames by reducing MAC retransmissions while minimizing any impact on perceptual video quality; and (b) It uses a group NACK-based Adaptive Window (NAW) of MAC frames to improve both throughput and delay performance in varying channel conditions. Through simulations and experiments, we observe 56--89% improvement in throughput and 34--48% improvement in delay performance over legacy DCF and 802.11e schemes. VMAC also shows 15--78% improvement over legacy schemes with multiple clients.
Automated Computational Cognitive-Modeling
Authors: Schaik Paul Van , Muzahir Raza Habib , Lockyer Mike
Published: June 2015

The information architecture of websites is the most important remaining source of usability problems. Therefore, this research explores automated cognitive computational analysis of the information architecture of large websites as a basis for improvement. To support goal-specific analysis, an enhanced model of web navigation was implemented with a novel database-oriented approach. Web navigation was simulated on the information architecture of two large sites. With the improved labeling system of the information architecture, simulation results showed a significant reduction in navigation problems. The results of two experiments demonstrate that sites with improved information architecture result in better outcomes of user information retrieval. Our database-oriented approach is extensible, allowing non-goal-specific analysis, modeling of nontext media content, and analysis of the organization- and navigation systems of information architectures.
Intelligibility Assessment and Speech Recognizer Word Accuracy Rate Prediction for Dysarthric Speakers in a Factor Analysis Subspace
Authors: Martínez David , Lleida Eduardo , Green Phil , Christensen Heidi , Ortega Alfonso , Miguel Antonio
Published: June 2015

Automated intelligibility assessments can support speech and language therapists in determining the type of dysarthria presented by their clients. Such assessments can also help predict how well a person with dysarthria might cope with a voice interface to assistive technology. Our approach to intelligibility assessment is based on
iVectors
, a set of measures that capture many aspects of a person’s speech, including intelligibility. The major advantage of
iVectors
is that they compress all acoustic information contained in an utterance into a reduced number of measures, and they are very suitable to be used with simple predictors. We show that intelligibility assessments work best if there is a pre-existing set of words annotated for intelligibility from the speaker to be evaluated, which can be used for training our system. We discuss the implications of our findings for practice.
LUCID
Authors: Turner Claude , Yan Jie , Richards Dwight , O'Brien Pamela , Odubiyi Jide , Brown Quincy
Published: June 2015

In this article, we discuss LUCID, a visualization and broadcast system targeted to improving a spectator's ability to understand and make sense of cyber defense competitions. The system aims to engage the spectator by presenting information pertinent to understanding the real-time events of the competition as they unfold. It accomplishes this through a combination of techniques, including real-time network security visualization, live video and audio monitoring, animation, computer graphics, user profiling, and commentary. We examine, specifically, how the LUCID system enables the audience to make sense of ongoing activities in a cyber defense competition.
On the Complexity of Probabilistic Abstract Argumentation Frameworks
Authors: Fazzinga Bettina , Flesca Sergio , Parisi Francesco
Published: June 2015

Probabilistic abstract argumentation combines Dung’s abstract argumentation framework with probability theory in order to model uncertainty in argumentation. In this setting, we address the fundamental problem of computing the probability that a set of arguments is an
extension
according to a given semantics. We focus on the most popular semantics (i.e.,
admissible
,
stable
,
complete
,
grounded
,
preferred
,
ideal-set
,
ideal
,
stage
, and
semistable
) and show the following dichotomy result: computing the probability that a set of arguments is an extension is either
FP
or
FP

#
P

-complete depending on the semantics adopted. Our polynomial-time results are particularly interesting, as they hold for some semantics for which no polynomial-time technique was known so far.
Evaluating a Collaborative iPad Game's Impact on Social Relationships for Children with Autism Spectrum Disorder
Authors: Boyd Louanne E. , Ringland Kathryn E. , Haimson Oliver L. , Fernandez Helen , Bistarkey Maria , Hayes Gillian R.
Published: June 2015

This article describes how collaborative assistive technologies, housed on off-the-shelf, low-cost platforms such as the iPad, can be used to facilitate social relationships in children with autism spectrum disorder (ASD). Through an empirical study of the use of a collaborative iPad game, Zody, we explore how assistive technologies can be used to support social relationships, even without intervention from adults. We discuss how specific design choices can encourage three levels of social relationship: membership, partnership, and friendship. This work contributes to research on both assistive technologies and collaborative gaming through a framework that describes how specific in-game elements can foster social skill development for children with ASD.
BLIS: A Framework for Rapidly Instantiating BLAS Functionality
Authors: Van Zee Field G. , van de Geijn Robert A.
Published: June 2015

The BLAS-like Library Instantiation Software (BLIS) framework is a new infrastructure for rapidly instantiating Basic Linear Algebra Subprograms (BLAS) functionality. Its fundamental innovation is that virtually all computation within level-2 (matrix-vector) and level-3 (matrix-matrix) BLAS operations can be expressed and optimized in terms of very simple kernels. While others have had similar insights, BLIS reduces the necessary kernels to what we believe is the simplest set that still supports the high performance that the computational science community demands. Higher-level framework code is generalized and implemented in ISO C99 so that it can be reused and/or reparameterized for different operations (and different architectures) with little to no modification. Inserting high-performance kernels into the framework facilitates the immediate optimization of any BLAS-like operations which are cast in terms of these kernels, and thus the framework acts as a productivity multiplier. Users of BLAS-dependent applications are given a choice of using the traditional Fortran-77 BLAS interface, a generalized C interface, or any other higher level interface that builds upon this latter API. Preliminary performance of level-2 and level-3 operations is observed to be competitive with two mature open source libraries (OpenBLAS and ATLAS) as well as an established commercial product (Intel MKL).
Sirius
Authors: Hauswald Johann , Laurenzano Michael A. , Zhang Yunqi , Li Cheng , Rovinski Austin , Khurana Arjun , Dreslinski Ronald G. , Mudge Trevor , Petrucci Vinicius , Tang Lingjia , Mars Jason
Published: June 2015

As user demand scales for intelligent personal assistants (IPAs) such as Apple's Siri, Google's Google Now, and Microsoft's Cortana, we are approaching the computational limits of current datacenter architectures. It is an open question how future server architectures should evolve to enable this emerging class of applications, and the lack of an open-source IPA workload is an obstacle in addressing this question. In this paper, we present the design of Sirius, an open end-to-end IPA web-service application that accepts queries in the form of voice and images, and responds with natural language. We then use this workload to investigate the implications of four points in the design space of future accelerator-based server architectures spanning traditional CPUs, GPUs, manycore throughput co-processors, and FPGAs.

To investigate future server designs for Sirius, we decompose Sirius into a suite of 7 benchmarks (Sirius Suite) comprising the computationally intensive bottlenecks of Sirius. We port Sirius Suite to a spectrum of accelerator platforms and use the performance and power trade-offs across these platforms to perform a total cost of ownership (TCO) analysis of various server design points. In our study, we find that accelerators are critical for the future scalability of IPA services. Our results show that GPU- and FPGA-accelerated servers improve the query latency on average by 10x and 16x. For a given throughput, GPU- and FPGA-accelerated servers can reduce the TCO of datacenters by 2.6x and 1.4x, respectively.
Memory Errors in Modern Systems
Authors: Sridharan Vilas , DeBardeleben Nathan , Blanchard Sean , Ferreira Kurt B. , Stearley Jon , Shalf John , Gurumurthi Sudhanva
Published: June 2015

Several recent publications have shown that hardware faults in the memory subsystem are commonplace. These faults are predicted to become more frequent in future systems that contain orders of magnitude more DRAM and SRAM than found in current memory subsystems. These memory subsystems will need to provide resilience techniques to tolerate these faults when deployed in high-performance computing systems and data centers containing tens of thousands of nodes. Therefore, it is critical to understand the efficacy of current hardware resilience techniques to determine whether they will be suitable for future systems. In this paper, we present a study of DRAM and SRAM faults and errors from the field. We use data from two leadership-class high-performance computer systems to analyze the reliability impact of hardware resilience schemes that are deployed in current systems. Our study has several key findings about the efficacy of many currently deployed reliability techniques such as DRAM ECC, DDR address/command parity, and SRAM ECC and parity. We also perform a methodological study, and find that counting errors instead of faults, a common practice among researchers and data center operators, can lead to incorrect conclusions about system reliability. Finally, we use our data to project the needs of future large-scale systems. We find that SRAM faults are unlikely to pose a significantly larger reliability threat in the future, while DRAM faults will be a major concern and stronger DRAM resilience schemes will be needed to maintain acceptable failure rates similar to those found on today's systems.
Improving Agility and Elasticity in Bare-metal Clouds
Authors: Omote Yushi , Shinagawa Takahiro , Kato Kazuhiko
Published: June 2015

Bare-metal clouds are an emerging infrastructure-as-a-service (IaaS) that leases physical machines (bare-metal instances) rather than virtual machines, allowing resource-intensive applications to have exclusive access to physical hardware. Unfortunately, bare-metal instances require time-consuming or OS-specific tasks for deployment due to the lack of virtualization layers, thereby sacrificing several beneficial features of traditional IaaS clouds such as agility, elasticity, and OS transparency. We present BMcast, an OS deployment system with a special-purpose de-virtualizable virtual machine monitor (VMM) that supports quick and OS-transparent startup of bare-metal instances. BMcast performs streaming OS deployment while allowing direct access to physical hardware from the guest OS, and then disappears after completing the deployment. Quick startup of instances improves agility and elasticity significantly, and OS transparency greatly simplifies management tasks for cloud customers. Experimental results have confirmed that BMcast initiated a bare-metal instance 8.6 times faster than image copying, and database performance on BMcast during streaming OS deployment was comparable to that on a state-of-the-art VMM without performing deployment. BMcast incurred zero overhead after de-virtualization.
CommGuard
Authors: Yetim Yavuz , Malik Sharad , Martonosi Margaret
Published: June 2015

As semiconductor technology scales towards ever-smaller transistor sizes, hardware fault rates are increasing. Since important application classes (e.g., multimedia, streaming workloads) are data-error-tolerant, recent research has proposed techniques that seek to save energy or improve yield by exploiting error tolerance at the architecture/microarchitecture level. Even seemingly error-tolerant applications, however, will crash or hang due to control-flow/memory addressing errors. In parallel computation, errors involving inter-thread communication can have equally catastrophic effects. Our work explores techniques that mitigate the impact of potentially catastrophic errors in parallel computation, while still garnering power, cost, or yield benefits from data error tolerance. Our proposed CommGuard solution uses FSM-based checkers to pad and discard data in order to maintain semantic alignment between program control flow and the data communicated between processors. CommGuard techniques are low overhead and they exploit application information already provided by some parallel programming languages (e.g. StreamIt). By converting potentially catastrophic communication errors into potentially tolerable data errors, CommGuard allows important streaming applications like JPEG and MP3 decoding to execute without crashing and to sustain good output quality, even for errors as frequent as every 500μs.
PuDianNao
Authors: Liu Daofu , Chen Tianshi , Liu Shaoli , Zhou Jinhong , Zhou Shengyuan , Teman Olivier , Feng Xiaobing , Zhou Xuehai , Chen Yunji
Published: June 2015

Machine Learning (ML) techniques are pervasive tools in various emerging commercial applications, but have to be accommodated by powerful computer systems to process very large data. Although general-purpose CPUs and GPUs have provided straightforward solutions, their energy-efficiencies are limited due to their excessive supports for flexibility. Hardware accelerators may achieve better energy-efficiencies, but each accelerator often accommodates only a single ML technique (family). According to the famous No-Free-Lunch theorem in the ML domain, however, an ML technique performs well on a dataset may perform poorly on another dataset, which implies that such accelerator may sometimes lead to poor learning accuracy. Even if regardless of the learning accuracy, such accelerator can still become inapplicable simply because the concrete ML task is altered, or the user chooses another ML technique.

In this study, we present an ML accelerator called PuDianNao, which accommodates seven representative ML techniques, including k-means, k-nearest neighbors, naive bayes, support vector machine, linear regression, classification tree, and deep neural network. Benefited from our thorough analysis on computational primitives and locality properties of different ML techniques, PuDianNao can perform up to 1056 GOP/s (e.g., additions and multiplications) in an area of 3.51 mm^2, and consumes 596 mW only. Compared with the NVIDIA K20M GPU (28nm process), PuDianNao (65nm process) is 1.20x faster, and can reduce the energy by 128.41x.
Asynchronized Concurrency
Authors: David Tudor , Guerraoui Rachid , Trigonakis Vasileios
Published: June 2015

We introduce "asynchronized concurrency (ASCY)," a paradigm consisting of four complementary programming patterns. ASCY calls for the design of concurrent search data structures (CSDSs) to resemble that of their sequential counterparts. We argue that ASCY leads to implementations which are portably scalable: they scale across different types of hardware platforms, including single and multi-socket ones, for various classes of workloads, such as read-only and read-write, and according to different performance metrics, including throughput, latency, and energy. We substantiate our thesis through the most exhaustive evaluation of CSDSs to date, involving 6 platforms, 22 state-of-the-art CSDS algorithms, 10 re-engineered state-of-the-art CSDS algorithms following the ASCY patterns, and 2 new CSDS algorithms designed with ASCY in mind. We observe up to 30% improvements in throughput in the re-engineered algorithms, while our new algorithms out-perform the state-of-the-art alternatives.
Beyond the PDP-11
Authors: Chisnall David , Rothwell Colin , Watson Robert N.M. , Woodruff Jonathan , Vadera Munraj , Moore Simon W. , Roe Michael , Davis Brooks , Neumann Peter G.
Published: June 2015

We propose a new memory-safe interpretation of the C abstract machine that provides stronger protection to benefit security and debugging. Despite ambiguities in the specification intended to provide implementation flexibility, contemporary implementations of C have converged on a memory model similar to the PDP-11, the original target for C. This model lacks support for memory safety despite well-documented impacts on security and reliability.

Attempts to change this model are often hampered by assumptions embedded in a large body of existing C code, dating back to the memory model exposed by the original C compiler for the PDP-11. Our experience with attempting to implement a memory-safe variant of C on the CHERI experimental microprocessor led us to identify a number of problematic idioms. We describe these as well as their interaction with existing memory safety schemes and the assumptions that they make beyond the requirements of the C specification. Finally, we refine the CHERI ISA and abstract model for C, by combining elements of the CHERI capability model and fat pointers, and present a softcore CPU that implements a C abstract machine that can run legacy C code with strong memory protection guarantees.
Supporting Differentiated Services in Computers via Programmable Architecture for Resourcing-on-Demand (PARD)
Authors: Ma Jiuyue , Sui Xiufeng , Sun Ninghui , Li Yupeng , Yu Zihao , Huang Bowen , Xu Tianni , Yao Zhicheng , Chen Yun , Wang Haibin , Zhang Lixin , Bao Yungang
Published: June 2015

This paper presents PARD, a programmable architecture for resourcing-on-demand that provides a new programming interface to convey an application's high-level information like quality-of-service requirements to the hardware. PARD enables new functionalities like fully hardware-supported virtualization and differentiated services in computers. PARD is inspired by the observation that a computer is inherently a network in which hardware components communicate via packets (e.g., over the NoC or PCIe). We apply principles of software-defined networking to this intra-computer network and address three major challenges. First, to deal with the semantic gap between high-level applications and underlying hardware packets, PARD attaches a high-level semantic tag (e.g., a virtual machine or thread ID) to each memory-access, I/O, or interrupt packet. Second, to make hardware components more manageable, PARD implements programmable control planes that can be integrated into various shared resources (e.g., cache, DRAM, and I/O devices) and can differentially process packets according to tag-based rules. Third, to facilitate programming, PARD abstracts all control planes as a device file tree to provide a uniform programming interface via which users create and apply tag-based rules.

Full-system simulation results show that by co-locating latencycritical memcached applications with other workloads PARD can improve a four-core computer's CPU utilization by up to a factor of four without significantly increasing tail latency. FPGA emulation based on a preliminary RTL implementation demonstrates that the cache control plane introduces no extra latency and that the memory control plane can reduce queueing delay for high-priority memory-access requests by up to a factor of 5.6.
Architectural Support for Software-Defined Metadata Processing
Authors: Dhawan Udit , Hritcu Catalin , Rubin Raphael , Vasilakis Nikos , Chiricescu Silviu , Smith Jonathan M. , Knight Thomas F. , Pierce Benjamin C. , DeHon Andre
Published: June 2015

Optimized hardware for propagating and checking software-programmable metadata tags can achieve low runtime overhead. We generalize prior work on hardware tagging by considering a generic architecture that supports software-defined policies over metadata of arbitrary size and complexity; we introduce several novel microarchitectural optimizations that keep the overhead of this rich processing low. Our model thus achieves the efficiency of previous hardware-based approaches with the flexibility of the software-based ones. We demonstrate this by using it to enforce four diverse safety and security policies---spatial and temporal memory safety, taint tracking, control-flow integrity, and code and data separation---plus a composite policy that enforces all of them simultaneously. Experiments on SPEC CPU2006 benchmarks with a PUMP-enhanced RISC processor show modest impact on runtime (typically under 10%) and power ceiling (less than 10%), in return for some increase in energy usage (typically under 60%) and area for on-chip memory structures (110%).
Nested Kernel
Authors: Dautenhahn Nathan , Kasampalis Theodoros , Dietz Will , Criswell John , Adve Vikram
Published: June 2015

Monolithic operating system designs undermine the security of computing systems by allowing single exploits anywhere in the kernel to enjoy full supervisor privilege. The nested kernel operating system architecture addresses this problem by "nesting" a small isolated kernel within a traditional monolithic kernel. The "nested kernel" interposes on all updates to virtual memory translations to assert protections on physical memory, thus significantly reducing the trusted computing base for memory access control enforcement. We incorporated the nested kernel architecture into FreeBSD on x86-64 hardware while allowing the entire operating system, including untrusted components, to operate at the highest hardware privilege level by write-protecting MMU translations and de-privileging the untrusted part of the kernel. Our implementation inherently enforces kernel code integrity while still allowing dynamically loaded kernel modules, thus defending against code injection attacks. We also demonstrate that the nested kernel architecture allows kernel developers to isolate memory in ways not possible in monolithic kernels by introducing write-mediation and write-logging services to protect critical system data structures. Performance of the nested kernel prototype shows modest overheads: <1% average for Apache and 2.7% for kernel compile. Overall, our results and experience show that the nested kernel design can be retrofitted to existing monolithic kernels, providing important security benefits.
GPU Concurrency
Authors: Alglave Jade , Batty Mark , Donaldson Alastair F. , Gopalakrishnan Ganesh , Ketema Jeroen , Poetzl Daniel , Sorensen Tyler , Wickerson John
Published: June 2015

Concurrency is pervasive and perplexing, particularly on graphics processing units (GPUs). Current specifications of languages and hardware are inconclusive; thus programmers often rely on folklore assumptions when writing software.

To remedy this state of affairs, we conducted a large empirical study of the concurrent behaviour of deployed GPUs. Armed with litmus tests (i.e. short concurrent programs), we questioned the assumptions in programming guides and vendor documentation about the guarantees provided by hardware. We developed a tool to generate thousands of litmus tests and run them under stressful workloads. We observed a litany of previously elusive weak behaviours, and exposed folklore beliefs about GPU programming---often supported by official tutorials---as false.

As a way forward, we propose a model of Nvidia GPU hardware, which correctly models every behaviour witnessed in our experiments. The model is a variant of SPARC Relaxed Memory Order (RMO), structured following the GPU concurrency hierarchy.