Computational performance of a parallelized three-dimensional high-order spectral element toolbox

In this paper, a comprehensive performance review of an MPI-based high-order three-dimensional spectral element method C++ toolbox is presented. The focus is put on the performance evaluation of several aspects with a particular emphasis on the parallel efficiency. The performance evaluation is analyzed with the help of a time prediction model based on a parameterization of the application and the hardware resources. Two tailor-made benchmark cases in computational fluid dynamics (CFD) are introduced and used to carry out this review, stressing the particular interest for clusters with up to thousands of cores. Some problems in the parallel implementation have been detected and corrected. The theoretical complexities with respect to the number of elements, to the polynomial degree, and to communication needs are correctly reproduced. It is concluded that this type of code has a nearly perfect speedup on machines with thousands of cores, and is ready to make the step to next-generation petaFLOP machines.     

Satellite-derived parameters for biological modelling in coastal waters: Illustration over the eastern continental shelf of the Bay of Biscay

In biological modelling of the coastal phytoplankton dynamics, the light attenuation coefficient is often expressed as a function of the concentrations of chlorophyll and mineral suspended particulate matter (SPM). In order to estimate the relationship between these parameters over the continental shelf of the northern Bay of Biscay, a set of in situ data has been gathered for the period 1998-2003 when SeaWiFS imagery is available. These data comprise surface measurements of the concentrations of total SPM, chlorophyll, and irradiance profiles from which is derived the attenuation coefficient of the photosynthetically available radiation, K_PAR. The performance of the IFREMER look-up table used to retrieve the chlorophyll concentration from the SeaWiFS radiance is evaluated on this new set of data. The quality of the estimated chlorophyll concentration is assessed from a comparison of the variograms of the in situ and satellite-derived chlorophyll concentrations. Once the chlorophyll concentration is determined, the non living SPM, which is defined as the SPM not related to the dead or alive endogenous phytoplankton, is estimated from the radiance at 555 nm by inverting a semi-analytic model. This method provides realistic estimations of concentrations of chlorophyll and SPM over the continental shelf all over the year. Finally, a relationship, based on non living SPM and chlorophyll, is proposed to estimate K_PAR on the continental shelf of the Bay of Biscay. The same formula is applied to non living SPM and chlorophyll concentrations, observed in situ or derived from SeaWiFS radiance.     

Data-parallel tomographic reconstruction: A comparison of filtered backprojection and direct Fourier reconstruction

We consider the parallelization of two standard 2D reconstruction algorithms, filtered backprojection and direct Fourier reconstruction, using the data-parallel programming style. The algorithms are implemented on a Connection Machine CM-5 with 16 processors and a peak performance of 2 Gflop/s.     

Ice sheet survey over Antarctica using satellite altimetry: ERS-2, Envisat,SARAL/AltiKa,the key importance of continuous observations along the same repeat orbit

From September 2002 to October 2010, the Envisat radar altimeter surveyed Greenland and Antarctica ice sheets on a 35 day repeat orbit, providing a unique data set for ice sheet mass balance studies. Up to 85 repeat cycles are available and the whole Envisat data set may be along-track processed in order to provide height variability and trend with a good spatial resolution for the objectives of ice sheet survey.

Soon, a joint Centre National d’Etudes Spatiales/Indian Space Research Organisation mission, SARAL (Satellite with Argos and AltiKa), with the AltiKa payload on board, will be launched on exactly the same orbit (less than 1 km of the nomimal orbit in the across-track direction). This will allow an extension of previous European Remote Sensing (ERS) satellite, ERS-1 and ERS-2, and Envisat missions of the European Space Agency (ESA), in particular from the point of view of ice altimetry. However, AltiKa operates in the Ka band (36.8 GHz), a higher frequency than the classical Ku band (13.6 GHz), leading to important modifications and potential improvements in the interactions between radar wave and snow-pack.

In this paper, a synthesis is presented of all available information relevant to ice altimetry scientific purposes as derived from the Envisat mission: mean and temporal derivatives of the height ? but also of the backscatter and of the two waveform parameters ? snow-pack change corrections, across-track surface slope at 1 km scale, etc. The spatial and temporal variability of ice sheet surface elevation is investigated with the help of the high-resolution Envisat along-track observations. We show that at least 50 repeat cycles are needed to reach the required accuracy for the elevation trend. It is thus advocated as potentially highly beneficial for SARAL/AltiKa as a follow-on mission. Moreover, the novel characteristics of SARAL/AltiKa are promising in improving our understanding of snow penetration impact.     

Parameter-insensitive kernel in extreme learning for non-linear support vector regression

Support vector regression (SVR) is a state-of-the-art method for regression which uses the ε‐sensitive loss and produces sparse models. However, non-linear SVRs are difficult to tune because of the additional kernel parameter. In this paper, a new parameter-insensitive kernel inspired from extreme learning is used for non-linear SVR. Hence, the practitioner has only two meta-parameters to optimise. The proposed approach reduces significantly the computational complexity yet experiments show that it yields performances that are very close from the state-of-the-art. Unlike previous works which rely on Monte-Carlo approximation to estimate the kernel, this work also shows that the proposed kernel has an analytic form which is computationally easier to evaluate.     

Concept drift and how to identify it

This paper studies concept drift over time. We first define the meaning of a concept in terms of intension, extension and label. Then we study concept drift over time using two theories: one based on concept identity and one based on concept morphing. A qualitative toolkit for analysing concept drift is proposed to detect concept shift and stability when concept identity is available, and concept split and strength of morphing chain if using the morphing theory. We apply our framework in four case-studies: a political vocabulary in SKOS, the DBpedia ontology in RDFS, the LKIF-Core ontology in OWL and a few biomedical ontologies in OBO. We describe ways of identifying interesting changes in the meaning of concept within given application contexts. These case-studies illustrate the feasibility of our framework in analysing concept drift in knowledge organisation schemas of varying expressiveness.     

A Rigorous Global Filtering Algorithm for Quadratic Constraints*

This article introduces a new filtering algorithm for handling systems of quadratic equations and inequations. Such constraints are widely used to model distance relations in numerous application areas ranging from robotics to chemistry. Classical filtering algorithms are based upon local consistencies and thus, are often unable to achieve a significant pruning of the domains of the variables occurring in quadratic constraint systems. The drawback of these approaches comes from the fact that the constraints are handled independently. We introduce here a global filtering algorithm that works on a tight linear relaxation of the quadratic constraints. The Simplex algorithm is then used to narrow the domains. Since most implementations of the Simplex work with floating point numbers and thus, are unsafe, we provide a procedure to generate safe linearizations. We also exploit a procedure provided by Neumaier and Shcherbina to get a safe objective value when calling the Simplex algorithm. With these two procedures, we prevent the Simplex algorithm from removing any solution while filtering linear constraint systems. Experimental results on classical benchmarks show that this new algorithm yields a much more effective pruning of the domains than local consistency filtering algorithms.*This article is an extended version of [23].     

An enhanced Web page change detection approach based on limiting similarity computations to elements of same type

This paper describes an efficient Web page detection approach based on restricting the similarity computations between two versions of a given Web page to the nodes with the same HTML tag type. Before performing the similarity computations, the HTML Web page is transformed into an XML-like structure in which a node corresponds to an open-closed HTML tag. Analytical expressions and supporting experimental results are used to quantify the improvements that are made when comparing the proposed approach to the traditional one, which computes the similarities across all nodes of both pages. It is shown that the improvements are highly dependent on the diversity of tags in the page. That is, the more diverse the page is (i.e., contains mixed content of text, images, links, etc.), the greater the improvements are, while the more uniform it is, the lesser they are.