High-Performance Interactive Scientific Visualization With Datoviz via the Vulkan Low-Level GPU API

International audienceWe reported initial work towards a new fast and scalable scientific visualization technology that leverages the Vulkan API to achieve unprecedented performance through GPUs. This technology is implemented in a C/C++ library called Datoviz that offers an intermediate-level API for scientific visualization libraries and software. Datoviz provides a unified graphics stack for 2-D, 3-D, graphical user interfaces, and natively supports efficient interactions between rendering and general-purpose GPU computing. A major direction of development is to investigate the integration of Datoviz as a low-level backend of a future version of VisPy, a popular Python scientific plotting library

Sustainable computational science: the ReScience initiative

Computer science o ers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel con dent their research is reproducible. But this is not exactly true. Jonathan Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. e actual scholarship is the full so ware environment, code, and data that produced the result. is implies new work ows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested, hardly ever actually executed to check that they produce the results advertised in the article. ReScience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically di erent from other traditional scienti c journals. ReScience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and so ware tests

IPython interactive computing and visualization cookbook

Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods

Why admitted cases of AHT make a low quality reference standard: A survey of people accused of AHT in France

Several influential articles that attempt to establish diagnostic methods for Abusive Head Trauma (AHT) use admitted cases as a reference standard. This study analyses a survey of people accused of AHT in France, to understand the environment and situations in which such admissions are made. Multiple reasons to question the reliability of admissions to AHT are demonstrated in the responses, including reduced sentences, the return of children to the family home, a desire to stop accusations being leveled at a partner and for legal proceedings to end. These factors must be considered in the context of proceedings that are long, expensive and stressful, leading to depression and financial hardship, and that seem to be inevitably heading towards conviction. The ineluctable conclusion is that admitted cases do not make a suitably reliable reference standard for undertaking scientific investigation, or for validating the diagnostic methods used for AHT

Rôle computationnel des corrélations dans le codage neuronal

Comprendre comment les fonctions mentales émergent des interactions entre neurones est un défi majeur des neurosciences modernes. Selon le point de vue classique, la fréquence de décharge est la seule variable pertinente pour le codage et la computation. Cependant, le développement de nouvelles techniques expérimentales a conduit à l'observation de corrélations omniprésentes dans le système nerveux. Leurs éventuels rôles computationnels sont incertains, et constitueraient un argument majeur en faveur du point du vue opposé, impulsionnel. L'objectif de cette thèse est d'apporter des éléments précisant ces rôles. D'abord, nous développons un outil informatique pour l'adaptation à des données de modèles impulsionnels. L'implémentation fait intervenir plusieurs techniques de calcul parallèle dont l'utilisation de cartes graphiques (GPU). Par ailleurs, nous étudions théoriquement et expérimentalement la détection de coïncidences dans un régime physiologique, correspondant à l'équilibre entre excitation et inhibition. Nous trouvons que les neurones corticaux sont extrêmement sensibles aux corrélations dans cette situation. Aussi, dans le but d'analyser nos données expérimentales, nous développons une nouvelle méthode de compensation dynamique d'électrode sans calibration. Nous montrons au final que la prise en compte des instants des potentiels d'action est indispensable pour la computation neuronale, et nous discutons des rôles computationnels possibles des corrélations.Understanding how mental functions emerge from the interactions between neurons is a major challenge in modern neuroscience. According to the classical point of view, the firing rate is the only relevant variable for neural coding and computation. However, the development of new experimental techniques has led to the observation of widespread neural correlations in the nervous system. Their possible computational roles are uncertain, and would favor the opposite point of view, namely the spike timing theory. The aim of this thesis is to bring new elements precising these roles. First, we develop a numerical toolbox for fitting spiking neuron models to electrophysiological data. Several parallel computing techniques are used, including an implementation on graphics processing units (GPU). Also, we theoretically and experimentally study the coincidence detection property of neurons in a physiological regime, corresponding to the balance between excitation and inhibition. We find that cortical neurons are extremely sensitive to input correlations in this situation. Also, in order to analyze our experimental data, we develop a new dynamic electrode compensation method that does not require calibration. In conclusion, we show that taking spike timing into account is necessary for understanding neural computation, and we discuss possible computational roles for neural correlations.PARIS-BIUSJ-Biologie recherche (751052107) / SudocSudocFranceF

VISPY, A Modern and Interactive Scientific Visualisation

International audienceWhereas the availability of data increases exponentially fast, the current visualization tools available today in Python do not scale gracefully to big data. The major plotting library in Python is Matplotlib and is more focused on the generation of static publication-ready figures than interactive visualization. These are really two different, and nearly orthogonal goals. For the former, high display quality is the major objective, whereas speed and reactivity is much more important for the latter. Matplotlib can be used for interactive visualization, but it has not been primarily designed for this. Consequently, the frame rate tends to be low on medium-size data sets, and million-points data sets can not be decently visualized in this way. Our goal is thus to create the foundations for the next-generation interactive visualization software in Python