Automatic Task-Based Code Generation for High Performance Domain Specific Embedded Language

Providing high level tools for parallel programming while sustaining a high level of performance has been a challenge that techniques like Domain Specific Embedded Languages try to solve. In previous works, we investigated the design of such a DSEL—NT\(^2\)—providing a Matlab -like syntax for parallel numerical computations inside a C++ library. In this paper, we show how NT\(^2\!\) has been redesigned for shared memory systems in an extensible and portable way. The new NT\(^2\!\) design relies on a tiered Parallel Skeleton system built using asynchronous task management and automatic compile-time taskification of user level code. We describe how this system can operate various shared memory runtimes and evaluate the design by using two benchmarks implementing linear algebra algorithms.     

The effect of the temporal resolution of NDVI data on season onset dates and trends across Canadian broadleaf forests

Satellite remote sensing has the potential to contribute to plant phenology monitoring at spatial and temporal scales relevant for regional and global scale studies. Historically, temporal composites of satellite data, ranging from 8 days to 16 days, have been used as a starting point for satellite-derived phenology data sets. In this study we assess how the temporal resolution of such composites affects the estimation of the start of season (SOS) by: 1) calibrating a relationship between satellite derived SOS with in situ leaf unfolding (LU) of trembling aspen (Populus tremuloides) across Canada and 2) quantifying the sensitivity of calibrated satellite SOS estimates and trends, over Canadian broadleaf forests, to the temporal resolution of NDVI data. SOS estimates and trends derived from daily NDVI data were compared to SOS estimates and trends derived from multiday NDVI composites that retain the exact date of the maximum NDVI value or that assume the midpoint of the multiday interval as the observation date. In situ observations of LU dates were acquired from the PlantWatch Canada network. A new Canadian database of cloud and snow screened daily 1-km resolution National Oceanic and Atmospheric Administration advanced very high resolution radiometer surface reflectance images was used as input satellite data. The mean absolute errors of SOS dates with respect to in situ LU dates ranged between 13 and 40 days. SOS estimates from NDVI composites that retain the exact date of the maximum NDVI value had smaller errors (~ 13 to 20 days). The sensitivity analysis reinforced these findings: SOS estimates from NDVI composites that use the exact date had smaller absolute deviations from the LU date (0 to − 5 days) than the SOS estimates from NDVI composites that use the midpoint (− 2 to − 27 days). The SOS trends between 1985 and 2007 were not sensitive to the temporal resolution or compositing methods. However, SOS trends at individual ecozones showed significant differences with the SOS trends from daily NDVI data (Taiga plains and the Pacific maritime zones). Overall, our results suggest that satellite based estimates of vegetation green-up dates should preferably use sub-sampled NDVI composites that include the exact observation date of the maximum NDVI to minimize errors in both, SOS estimates and SOS trend analyses. For trend analyses alone, any of the compositing methods could be used, preferably with composite intervals of less than 28 days. This is an important finding, as it suggests that existing long-term 10-day or 15-day NDVI composites could be used for SOS trend analyses over broadleaf forests in Canada or similar areas. Future studies will take advantage of the growing in situ phenology networks to improve the validation of satellite derived green-up dates.     

Fitting a Step Function to a Point Set

We consider the problem of fitting a step function to a set of points. More precisely, given an integer k and a set P of n points in the plane, our goal is to find a step function f with k steps that minimizes the maximum vertical distance between f and all the points in P. We first give an optimal Θ(nlog n) algorithm for the general case. In the special case where the points in P are given in sorted order according to their x-coordinates, we give an optimal Θ(n) time algorithm. Then, we show how to solve the weighted version of this problem in time O(nlog ⁴ n). Finally, we give an O(nh ²log n) algorithm for the case where h outliers are allowed. The running time of all our algorithms is independent of k.     

Utilizing endoscopic technology to reveal real-time proteomic alterations in response to chemoprevention

Cancer chemoprevention approaches use either pharmacological or dietary agents to impede, arrest or reverse the carcinogenic process. Although several agents have shown effectiveness against colon cancer, present intervention strategies provide only partial reduction. In this study, we utilized high-resolution endoscopy to obtain colon tumor biopsy specimens from Apc mutant mice before and after 2-wk sulindac intervention. To acquire information beyond genomics, proteome analysis using the ProteomeLab PF2D platform was implemented to generate 2-D protein expression maps from biopsies. Chromatograms produced common signature profiles between sulindac and nonsulindac treated samples, and contrasting profiles termed "fingerprints". We selected a double peak that appeared in tumor biopsies from sulindac-treated mice. Further analyses using MS sequencing identified this protein as histone H2B. The location of H2B in the 1(st) dimension strongly suggested PTM, consistent with identification of two oxidized methionines. While further studies on sulindac proteomic fingerprints are underway, this study demonstrates the feasibility and advantages of "real-time" proteomic analysis for obtaining information on biomarker discovery and drug activity that would not be revealed by a genetic assay. This approach should be broadly applicable for assessing lesion responsiveness in a wide range of translational and human clinical studies.     

Recognizable trace languages,distributed automata and the distribution problem

We introduce new finite state parallel machines, the (-)distributed automata, for trace languages. We prove that these machines give a new characterization of recognizable trace languages: a trace language is recognizable if and only if it is recognized by a (-)distributed automaton. At last, we show how the classical problem of distribution of uninterpreted tasks on several processors can be straightforward modelized by recognizable trace languages and solved using (-)distributed.This work has been partly supported by the ESPRIT Basic Research Actions N^o 3148 (DEMON) and by the PRC C³ and Math-Info     

Using retina modelling to characterize blinking: comparison between EOG and video analysis

A large number of car crashes are caused by drowsiness every year. The analysis of eye blinks provides reliable information about drowsiness. This paper proposes to study the relation between electrooculogram (EOG) and video analysis for blink detection and characterization. An original method to detect and characterize blinks from a video analysis is presented here. The method uses different filters based on the human retina modelling. A illumination robust filter is first used to normalize illumination variations of the video input. Then, Outer and an Inner Plexiform Layer filters are used to extract energy signals from eye area. The eye detection is processed mixing gradient and projection methods which makes it able to detect even closed eyes. The illumination robust filter makes it possible to detect the eyes even in night conditions, without using external lighting. The video analysis extracts two signals from the eye area measuring the quantity of static edges and moving edges. Blinks are then detected and characterized from these two signals. A comparison between the features extracted from the EOG and the same features extracted from the video analysis is then performed on a database of 14 different people. This study shows that some blink features extracted from the video are highly correlated with their EOG equivalent: the duration, the duration at 50%, the frequency, the percentage of eye closure at 80% and the amplitude velocity ratio. The frame rate influence on the accuracy of the different features extracted is also studied and enlightens on the need of a high frame rate camera to detect and characterize accurately blinks from a video analysis.     

Desynchronization and inhibition of Kuramoto oscillators by scalar mean-field feedback

Motivated by neuroscience applications, and in particular by the deep brain stimulation treatment for Parkinson’s disease, we have recently derived a simplified model of an interconnected neuronal population under the effect of its mean-field proportional feedback. In this paper, we rely on that model to propose conditions under which proportional mean-field feedback achieves either oscillation inhibition or desynchronization. More precisely, we show that for small natural frequencies, this scalar control signal induces an inhibition of the collective oscillation. For the closed-loop system, this situation corresponds to a fixed point which is shown to be almost globally asymptotically stable in the fictitious case of zero natural frequencies and all-to-all coupling and feedback. In the case of an odd number of oscillators, this property is shown to be robust to small natural frequencies and heterogencities in both the coupling and feedback topology. On the contrary, for large natural frequencies, we show that scalar proportional mean-field feedback is able to induce desynchronization. After having recalled a formal definition for desynchronization, we show how it can be induced in a network of originally synchronized oscillators.     

Effective discrepancy and numerical experiments

Many problems require the computation of a high dimensional integral, typically with a few tens of input factors, with a low number of integrand evaluations. To avoid the curse of dimensionality, we reduce the dimension before applying the Quasi-Monte Carlo method. We will show how to reduce the dimension by computing approximate Sobol indices of the variables with a two-levels fractional factorial design. Then, we will use the Sobol indices to define the effective discrepancy, which turns out to be correlated with the QMC error and thus enables one to choose a good sequence for the integral estimation.     

An algebraic approach to data languages and timed languages

Algebra offers an elegant and powerful approach to understand regular languages and finite automata. Such framework has been notoriously lacking for timed languages and timed automata. We introduce the notion of monoid recognizability for data languages, which includes timed languages as special case, in a way that respects the spirit of the classical situation. We study closure properties and hierarchies in this model and prove that emptiness is decidable under natural hypotheses. Our class of recognizable languages properly includes many families of deterministic timed languages that have been proposed until now, and the same holds for non-deterministic versions.     

Monitoring of multivariable dynamic processes and sensor auditing

Industrial continuous processes are usually operated under closed-loop control, yielding process measurements that are autocorrelated, cross correlated, and collinear. A statistical process monitoring (SPM) method based on state variables is introduced to monitor such processes. The statistical model that describes the in-control variability is based on a canonical variate (CV) state space model. The CV state variables are linear combinations of the past process measurements which explain the variability of the future measurements the most, and they are regarded as the principal dynamic dimensions. A T² statistic based on the CV state variables is utilized for developing the SPM procedure. The CV state variables are also used for monitoring sensor reliability. An experimental application to a high temperature short time (HTST) pasteurization process illustrates the proposed methodology.