pinecone/core-2020-05-10-deduplication huggingface dataset:
Leveraging Cloud Heterogeneity for Cost-Efficient Execution of Parallel Applications

Public cloud providers offer a wide range of instance types, with different processing and interconnection speeds, as well as varying prices. Furthermore, the tasks of many parallel applications show different computational demands due to load imbalance. These differences can be exploited for improving the cost efficiency of parallel applications in many cloud environments by matching application requirements to instance types. In this paper, we introduce the concept of heterogeneous cloud systems consisting of different instance types to leverage the different computational demands of large parallel applications for improved cost efficiency. We present a mechanism that automatically suggests a suitable combination of instances based on a characterization of the application and the instance types. With such a heterogeneous cloud, we are able to improve cost efficiency significantly for a variety of MPI-based applications, while maintaining a similar performance.Peer ReviewedPostprint (author's final draft
Supporting the Xeon Phi coprocessor in a Heterogeneous Programming Model

Producción CientíficaSupercomputers are becoming more heterogeneous. They are composed by several machines with different computation capabilities and different kinds and families of accelerators, such as GPUs or Intel Xeon Phi coprocessors. Programming these machines is a hard task, that requires a deep study of the architectural details, in order to exploit efficiently each computational unit.

In this paper, we present an extension of a GPU-CPU heterogeneous programming model, to include support for Intel Xeon Phi coprocessors. This contribution extends the previous model and its implementation, by taking advantage of both the GPU communication model and the CPU execution model of the original approach, to derive a new approach for the Xeon Phi. Our experimental results show that using our approach, the programming effort needed for changing the kind of target devices is highly reduced for several study cases. For example, using our model to program a Mandelbrot benchmark, the 97% of the application code is reused between a GPU implementation and a Xeon Phi implementation.MICINN (Spain) and ERDF program of the European Union: HomProg-HetSys project (TIN2014-58876-P), and COST Program Action IC1305: Network for Sustainable Ultrascale Computing (NESUS)
To distribute or not to distribute: The question of load balancing for performance or energy

Heterogeneous systems are nowadays a common choice in the path to Exascale. Through the use of accelerators they offer outstanding energy efficiency. The programming of these devices employs the host-device model, which is suboptimal as CPU remains idle during kernel executions, but still consumes energy. Making the CPU contribute computin effort might improve the performance and energy consumption of the system. This paper analyses the advantages of this approach and sets the limits of when its beneficial. The claims are supported by a set of models that determine how to share a single data-parallel task between the CPU and the accelerator for optimum performance, energy consumption or efficiency. Interestingly, the models show that optimising performance does not always mean optimum energy or efficiency as well. The paper experimentally validates the models, which represent an invaluable tool for programmers when faced with the dilemma of whether to distribute their workload in these systems.This work has been supported by the University of Cantabria (CVE-2014-18166), the Spanish Science and Technology Commission (TIN2016-76635-C2-2-R), the European Research Council (G.A. No 321253) and the European HiPEAC Network of Excellence. The Mont-Blanc project has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 671697.Peer ReviewedPostprint (author's final draft
Coverage of ISO/IEC 29110 project management process of basic profile by a serious game.

The ISO/IEC 29110 standard aims to assist and encourage Very Small Entities (VSEs) in understanding, adopting, assessing and improving their software processes to their specific needs. Although the integration of international software standards in VSEs is a relevant topic, the learning/teaching process are a considerable challenge for industrial trainers, practitioners and VSEs. In this paper, we analyze the Project Management process of the Basic Profile of the ISO/IEC 29110 and propose a simulation-based serious game for supporting the learning/teaching process of the standard. The paper provides a mapping between the different stages of the game lifecycle and the Project Management process the standard. Moreover, we present the results of a preliminary study to assess the idea of using the proposed serious game for supporting software process education, which allows getting an initial positive evidence about the potential of the game for helping to understand the Project Management process of the standard
Examining reward mechanisms for effective usage of application lifecycle management tools

Application lifecycle management (ALM) highlights the rules of the road for the entire software ecosystems’ lifecycle. Successful ALM enables clarity around the entire delivery effort, from defining requirements to deploying the software product. One of the challenges in software engineering today is to orchestrate ALM tools to a set of software projects effectively.  In particular, it is challenging for software practitioners to continuously fully engage with the tasks that are assigned to them. The goal of this study is to address such situations using a game theoretic approach by utilizing a reward mechanism, which we intent to test in a medium-sized software development organization. Based on a set of game elements, this study proposes an auction mechanism to address human resource allocation and task optimization issues, and consequently tackle the potential problem of software practitioners’ engagement
A reliability-based approach for influence maximization using the
  evidence theory

The influence maximization is the problem of finding a set of social network
users, called influencers, that can trigger a large cascade of propagation.
Influencers are very beneficial to make a marketing campaign goes viral through
social networks for example. In this paper, we propose an influence measure
that combines many influence indicators. Besides, we consider the reliability
of each influence indicator and we present a distance-based process that allows
to estimate the reliability of each indicator. The proposed measure is defined
under the framework of the theory of belief functions. Furthermore, the
reliability-based influence measure is used with an influence maximization
model to select a set of users that are able to maximize the influence in the
network. Finally, we present a set of experiments on a dataset collected from
Twitter. These experiments show the performance of the proposed solution in
detecting social influencers with good quality.Comment: 14 pages, 8 figures, DaWak 2017 conferenc
MDA-based approach for NoSQL Databases Modelling

It is widely accepted today that relational systems are not appropriate to handle Big Data. This has led to a new category of databases commonly known as NoSQL databases that were created in response to the needs for better scalability, higher flexibility and faster data access. These systems have proven their efficiency to store and query Big Data. Unfortunately, only few works have presented approaches to implement conceptual models describing Big Da-ta in NoSQL systems. This paper proposes an automatic MDA-based approach that provides a set of transformations, formalized with the QVT language, to translate UML conceptual models into NoSQL models. In our approach, we build an intermediate logical model compatible with column, document and graph oriented systems. The advantage of using a unified logical model is that this model remains stable, even though the NoSQL system evolves over time which simplifies the transformation process and saves developers efforts and time
Modeling magnetospheric fields in the Jupiter system

The various processes which generate magnetic fields within the Jupiter
system are exemplary for a large class of similar processes occurring at other
planets in the solar system, but also around extrasolar planets. Jupiter's
large internal dynamo magnetic field generates a gigantic magnetosphere, which
is strongly rotational driven and possesses large plasma sources located deeply
within the magnetosphere. The combination of the latter two effects is the
primary reason for Jupiter's main auroral ovals. Jupiter's moon Ganymede is the
only known moon with an intrinsic dynamo magnetic field, which generates a
mini-magnetosphere located within Jupiter's larger magnetosphere including two
auroral ovals. Ganymede's magnetosphere is qualitatively different compared to
the one from Jupiter. It possesses no bow shock but develops Alfv\'en wings
similar to most of the extrasolar planets which orbit their host stars within
0.1 AU. New numerical models of Jupiter's and Ganymede's magnetospheres
presented here provide quantitative insight into the processes that maintain
these magnetospheres. Jupiter's magnetospheric field is approximately
time-periodic at the locations of Jupiter's moons and induces secondary
magnetic fields in electrically conductive layers such as subsurface oceans. In
the case of Ganymede, these secondary magnetic fields influence the oscillation
of the location of its auroral ovals. Based on dedicated Hubble Space Telescope
observations, an analysis of the amplitudes of the auroral oscillations
provides evidence that Ganymede harbors a subsurface ocean. Callisto in
contrast does not possess a mini-magnetosphere, but still shows a perturbed
magnetic field environment. Callisto's ionosphere and atmospheric UV emission
is different compared to the other Galilean satellites as it is primarily been
generated by solar photons compared to magnetospheric electrons.Comment: Chapter for Book: Planetary Magnetis
Structural Change in (Economic) Time Series

Methods for detecting structural changes, or change points, in time series
data are widely used in many fields of science and engineering. This chapter
sketches some basic methods for the analysis of structural changes in time
series data. The exposition is confined to retrospective methods for univariate
time series. Several recent methods for dating structural changes are compared
using a time series of oil prices spanning more than 60 years. The methods
broadly agree for the first part of the series up to the mid-1980s, for which
changes are associated with major historical events, but provide somewhat
different solutions thereafter, reflecting a gradual increase in oil prices
that is not well described by a step function. As a further illustration, 1990s
data on the volatility of the Hang Seng stock market index are reanalyzed.Comment: 12 pages, 6 figure
Hadamard States From Light-like Hypersurfaces

This book provides a rather self-contained survey of the construction of
Hadamard states for scalar field theories in a large class of notable
spacetimes, possessing a (conformal) light-like boundary. The first two
sections focus on explaining a few introductory aspects of this topic and on
providing the relevant geometric background material. The notions of
asymptotically flat spacetimes and of expanding universes with a cosmological
horizon are analysed in detail, devoting special attention to the
characterization of asymptotic symmetries. In the central part of the book, the
quantization of a real scalar field theory on such class of backgrounds is
discussed within the framework of algebraic quantum field theory. Subsequently
it is explained how it is possible to encode the information of the observables
of the theory in a second, ancillary counterpart, which is built directly on
the conformal (null) boundary. This procedure, dubbed bulk-to-boundary
correspondence, has the net advantage of allowing the identification of a
distinguished state for the theory on the boundary, which admits a counterpart
in the bulk spacetime which is automatically of Hadamard form. In the last part
of the book, some applications of these states are discussed, in particular the
construction of the algebra of Wick polynomials. This book is aimed mainly, but
not exclusively, at a readership with interest in the mathematical formulation
of quantum field theory on curved backgrounds.Comment: 106 pages, 2 figures, to appear in SpringerBriefs in Mathematical
  Physics, references adde
How to leverage reflection in case of inquiry learning? The study of awareness tools in the context of virtual and remote laboratory

In this paper we design a set of awareness and reflection tools aiming at engaging learners in the deep learning process during a practical activity carried out through a virtual and remote laboratory. These tools include: (i) a social awareness tool revealing to learners their current and general levels of performance, but also enabling the comparison between their own and their peers’ performance; (ii) a reflection-on-action tool, implemented as timelines, allowing learners to deeply analyze both their own completed work and the tasks achieved by peers; (iii) a reflection-in-action tool acting as a live video player to let users easily see what others are doing. An experimentation involving 80 students was conducted in an authentic learning setting about operating system administration; the participants evaluated the system only slightly higher than traditional computational environments when it comes to leverage reflection and critical thinking, even if they evaluated the system as good in terms of usability
Optimal a priori error estimates of parabolic optimal control problems
  with a moving point control

In this paper we consider a parabolic optimal control problem with a Dirac
type control with moving point source in two space dimensions. We discretize
the problem with piecewise constant functions in time and continuous piecewise
linear finite elements in space. For this discretization we show optimal order
of convergence with respect to the time and the space discretization parameters
modulo some logarithmic terms. Error analysis for the same problem was carried
out in the recent paper [17], however, the analysis there contains a serious
flaw. One of the main goals of this paper is to provide the correct proof. The
main ingredients of our analysis are the global and local error estimates on a
curve, that have an independent interest
An agent-based approach for the dynamic and decentralized service reconfiguration in collaborative production scenarios

Future industrial systems endorse the implementation of innovative paradigms addressing the continuous flexibility, reconfiguration, and evolution to face the volatility of dynamic markets demanding complex and customized products. Smart manufacturing relies on the capability to adapt and evolve to face changes, particularly by identifying, on-the-fly, opportunities to reconfigure its behavior and functionalities and offer new and more adapted services. This paper introduces an agent-based approach for service reconfiguration that allows the identification of the opportunities for reconfiguration in a pro-active and dynamic manner, and the implementation on-the-fly of the best strategies for the service reconfiguration that will lead to a better production efficiency. The developed prototype for a flexible manufacturing system case study allowed to verify the feasibility of greedy local service reconfiguration for competitive and collaborative industrial automation situations.info:eu-repo/semantics/publishedVersio
An Integrated Research Infrastructure for Validating Cyber-Physical
  Energy Systems

Renewables are key enablers in the plight to reduce greenhouse gas emissions
and cope with anthropogenic global warming. The intermittent nature and limited
storage capabilities of renewables culminate in new challenges that power
system operators have to deal with in order to regulate power quality and
ensure security of supply. At the same time, the increased availability of
advanced automation and communication technologies provides new opportunities
for the derivation of intelligent solutions to tackle the challenges. Previous
work has shown various new methods of operating highly interconnected power
grids, and their corresponding components, in a more effective way. As a
consequence of these developments, the traditional power system is being
transformed into a cyber-physical energy system, a smart grid. Previous and
ongoing research have tended to mainly focus on how specific aspects of smart
grids can be validated, but until there exists no integrated approach for the
analysis and evaluation of complex cyber-physical systems configurations. This
paper introduces integrated research infrastructure that provides methods and
tools for validating smart grid systems in a holistic, cyber-physical manner.
The corresponding concepts are currently being developed further in the
European project ERIGrid.Comment: 8th International Conference on Industrial Applications of Holonic
  and Multi-Agent Systems (HoloMAS 2017
Simulation-based Validation of Smart Grids - Status Quo and Future
  Research Trends

Smart grid systems are characterized by high complexity due to interactions
between a traditional passive network and active power electronic components,
coupled using communication links. Additionally, automation and information
technology plays an important role in order to operate and optimize such
cyber-physical energy systems with a high(er) penetration of fluctuating
renewable generation and controllable loads. As a result of these developments
the validation on the system level becomes much more important during the whole
engineering and deployment process, today. In earlier development stages and
for larger system configurations laboratory-based testing is not always an
option. Due to recent developments, simulation-based approaches are now an
appropriate tool to support the development, implementation, and roll-out of
smart grid solutions. This paper discusses the current state of
simulation-based approaches and outlines the necessary future research and
development directions in the domain of power and energy systems.Comment: 8th International Conference on Industrial Applications of Holonic
  and Multi-Agent Systems (HoloMAS 2017
Prediction models for short-term load and production forecasting in smart electrical grids

The scheduling of household smart load devices play a key
role in microgrid ecosystems, and particularly in underpowered grids.
The management and sustainability of these microgrids could bene t
from the application of short-term prediction for the energy production
and demand, which have been successfully applied and matured in
larger scale systems, namely national power grids. However, the dynamic
change of energy demand, due to the necessary adjustments aiming to
render the microgrid self-sustainability, makes the forecasting process
harder. This paper analyses some prediction techniques to be embedded
in intelligent and distributed agents responsible to manage electrical
microgrids, and especially increase their self-sustainability. These prediction
techniques are implemented in R language and compared according
to di erent prediction and historical data horizons. The experimental results
shows that none is the optimal solution for all criteria, but allow to
identify the best prediction techniques for each scenario and time scope.info:eu-repo/semantics/publishedVersio
Validating Intelligent Power and Energy Systems - A Discussion of
  Educational Needs

Traditional power systems education and training is flanked by the demand for
coping with the rising complexity of energy systems, like the integration of
renewable and distributed generation, communication, control and information
technology. A broad understanding of these topics by the current/future
researchers and engineers is becoming more and more necessary. This paper
identifies educational and training needs addressing the higher complexity of
intelligent energy systems. Education needs and requirements are discussed,
such as the development of systems-oriented skills and cross-disciplinary
learning. Education and training possibilities and necessary tools are
described focusing on classroom but also on laboratory-based learning methods.
In this context, experiences of using notebooks, co-simulation approaches,
hardware-in-the-loop methods and remote labs experiments are discussed.Comment: 8th International Conference on Industrial Applications of Holonic
  and Multi-Agent Systems (HoloMAS 2017
Boron isotopes in foraminifera : systematics, biomineralisation, and CO2 reconstruction

Funding: Fellowship from University of St Andrews, $100 (pending) from Richard Zeebe, UK NERC grants NE/N003861/1 and NE/N011716/1.The boron isotope composition of foraminifera provides a powerful tracer for CO2 change over geological time. This proxy is based on the equilibrium of boron and its isotopes in seawater, which is a function of pH. However while the chemical principles underlying this proxy are well understood, its reliability has previously been questioned, due to the difficulty of boron isotope (δ11B) analysis on foraminferal samples and questions regarding calibrations between δ11B and pH. This chapter reviews the current state of the δ11B-pH proxy in foraminfera, including the pioneering studies that established this proxy’s potential, and the recent work that has improved understanding of boron isotope systematics in foraminifera and applied this tracer to the geological record. The theoretical background of the δ11B-pH proxy is introduced, including an accurate formulation of the boron isotope mass balance equations. Sample preparation and analysis procedures are then reviewed, with discussion of sample cleaning, the potential influence of diagenesis, and the strengths and weaknesses of boron purification by column chromatography versus microsublimation, and analysis by NTIMS versus MC-ICPMS. The systematics of boron isotopes in foraminifera are discussed in detail, including results from benthic and planktic taxa, and models of boron incorporation, fractionation, and biomineralisation. Benthic taxa from the deep ocean have δ11B within error of borate ion at seawater pH. This is most easily explained by simple incorporation of borate ion at the pH of seawater. Planktic foraminifera have δ11B close to borate ion, but with minor offsets. These may be driven by physiological influences on the foraminiferal microenvironment; a novel explanation is also suggested for the reduced δ11B-pH sensitivities observed in culture, based on variable calcification rates. Biomineralisation influences on boron isotopes are then explored, addressing the apparently contradictory observations that foraminifera manipulate pH during chamber formation yet their δ11B appears to record the pH of ambient seawater. Potential solutions include the influences of magnesium-removal and carbon concentration, and the possibility that pH elevation is most pronounced during initial chamber formation under favourable environmental conditions. The steps required to reconstruct pH and pCO2 from δ11B are then reviewed, including the influence of seawater chemistry on boron equilibrium, the evolution of seawater δ11B, and the influence of second carbonate system parameters on δ11B-based reconstructions of pCO2. Applications of foraminiferal δ11B to the geological record are highlighted, including studies that trace CO2 storage and release during recent ice ages, and reconstructions of pCO2 over the Cenozoic. Relevant computer codes and data associated with this article are made available online.Publisher PDFPeer reviewe