SPDF: A Schedulable Parametric Data-Flow MoC

International audienceDataflow programming models are suitable to express multi-core streaming applications. The design of high- quality embedded systems in that context requires static analysis to ensure the liveness and bounded memory of the application. However, many streaming applications have a dynamic behavior. The previously proposed dataflow models for dynamic applications do not provide any static guarantees or only in exchange of significant restrictions in expressive power or automation. To overcome these restrictions, we propose the schedulable parametric dataflow (SPDF) model. We present static analyses and a quasi-static scheduling algorithm. We demonstrate our approach using a video decoder case study

SPDF: A Schedulable Parametric Data-Flow MoC (Extended Version)

Dataflow programming models are suitable to express multi-core streaming applications. The design of high-quality embedded systems in that context requires static analysis to ensure the liveness and bounded memory of the application. However, many streaming applications have a dynamic behavior. The previously proposed dataflow models for dynamic applications do not provide any static guarantees or only in exchange of significant restrictions in expressive power or automation. To overcome these restrictions, we propose the schedulable parametric dataflow (SPDF) model of computation. We present static analyses and a quasi-static scheduling algorithm. We demonstrate our approach using a video decoder case study

Time-redundancy Transformations for Adaptive Fault-Tolerant Circuits

Abstract-We present a novel logic-level circuit transformation technique for the automatic insertion of fault-tolerance properties. The transformations, based on time-redundancy, allow dynamically changes of the level of redundancy without interrupting the computation. The proposed concept of dynamic time redundancy permits adaptive circuits whose fault-tolerance properties can be "on-the-fly" traded-off for throughput. The approach is technologically independent and does not require any specific hardware support. Experimental results on the ITC'99 benchmark suite indicate that the benefits of our method grow with the combinational size of the circuit. Dynamic double and triple time redundant transformations generate circuits 1.7 to 2.9 times smaller than full Triple-Modular Redundancy (TMR). This transformation is a good alternative to TMR for logicintensive safety-critical circuits where low hardware overhead or only temporary fault-tolerance guarantees are needed

High infiltration of CD209+ dendritic cells and CD163+ macrophages in the peritumor area of prostate cancer is predictive of late adverse outcomes

IntroductionProstate cancer (PCa) shows considerable variation in clinical outcomes between individuals with similar diseases. The initial host-tumor interaction as assessed by detailed analysis of tumor infiltrating immune cells within the primary tumor may dictate tumor evolution and late clinical outcomes. In this study, we assessed the association between clinical outcomes and dendritic cell (DC) or macrophage (MΦ) tumor infiltration as well as with expression of genes related to their functions.MethodsInfiltration and localization of immature DC, mature DC, total MΦ and M2-type MΦ was analyzed by immunohistochemistry in 99 radical prostatectomy specimens from patients with 15.5 years median clinical follow-up using antibodies against CD209, CD83, CD68 and CD163, respectively. The density of positive cells for each marker in various tumor areas was determined. In addition, expression of immune genes associated with DC and MΦ was tested in a series of 50 radical prostatectomy specimens by Taqman Low-Density Array with similarly long follow-up. Gene expression was classified as low and high after unsupervised hierarchical clustering. Numbers and ratio of positive cells and levels of gene expression were correlated with endpoints such as biochemical recurrence (BCR), need for definitive androgen deprivation therapy (ADT) or lethal PCa using Cox regression analyses and/or Kaplan-Meier curves.ResultsPositive immune cells were observed in tumor, tumor margin, and normal-like adjacent epithelium areas. CD209+ and CD163+ cells were more abundant at the tumor margin. Higher CD209+/CD83+ cell density ratio at the tumor margin was associated with higher risk of ADT and lethal PCa while higher density of CD163+ cells in the normal-like adjacent epithelium was associated with a higher risk of lethal PCa. A combination of 5 genes expressed at high levels correlated with a shorter survival without ADT and lethal PCa. Among these five genes, expression of IL12A and CD163 was correlated to each other and was associated with shorter survival without BCR and ADT/lethal PCa, respectively.ConclusionA higher level of infiltration of CD209+ immature DC and CD163+ M2-type MΦ in the peritumor area was associated with late adverse clinical outcomes

RDF : un modèle flot de données reconfigurable(version étendue)

Dataflow Models of Computation (MoCs) are widely used in embedded systems, including multimedia processing, digital signal processing, telecommunications, and automatic control. In a dataflow MoC, an application is specified as a graph of actors connected by FIFO channels. One of the most popular dataflow MoCs, Synchronous Dataflow (SDF), provides static analyses to guarantee boundedness and liveness, which are key properties for embedded systems. However, SDF (and most of its variants) lacks the capability to express the dynamism needed by modern streaming applications. In particular, the applications mentioned above have a strong need for reconfigurability to accommodate changes in the input data, the control objectives, or the environment.We address this need by proposing a new MoC called Reconfigurable Dataflow (RDF). RDF extends SDF with transformation rules that specify how the topology and actors of the graph may be reconfigured. Starting from an initial RDF graph and a set of transformation rules, an arbitrary number of new RDF graphs can be generated at runtime. A key feature of RDF is that it can be statically analyzed to guarantee that all possible graphs generated at runtime will be consistent and live. We introduce the RDF MoC, describe its associated static analyses, and outline its implementation.Les modèles de calcul (MoCs) flot de données synchrones sont très utilisés dans les systèmes embarqués pour les applications multimédia, de traitement du signal, de télécommunication et de contrôle automatique. Dans ce style de modèle, une application est spécifiée par un graphe d’acteurs connectés par des liens FIFO de communication. Un des MoCs les plus connus, SDF (pour Synchronous Dataflow), permet des analyses statiques qui garantissent l’exécution enmémoire bornée et l’absence d’interblocage, propriétés clés pour les systèmes embarqués. Néanmoins, SDF (et la plupart de ses variantes) ne permet pas d’exprimer la dynamicité requise par les applications embarquées modernes. En particulier, ces applications ont souvent besoin de se reconfigurer pour s’adapter aux changements (par ex., de débit ou de qualité) du flot d’entrée, des objectifs de contrôle ou de l’environnement.Afin de répondre à ce besoin, nous proposons le MoC RDF (pour Reconfigurable DataFlow) qui étend SDF avec des règles de transformations spécifiant comment la topologie et les acteurs du graphe peuvent être reconfigurés dynamiquement. En considérant un graphe SDF initial et un ensemble de règles de transformation, un nombre arbitraire de nouveaux graphes peuvent être produits. La principale qualité de RDF est qu’il peut être analysé statiquement pour garantir que tous les graphes générés dynamiquement s’exécuteront en mémoire bornée et sans interblocage.Nous présentons le modèle RDF, décrivons les analyses statiques associées et décrivons brièvementson implémentation

RDF: Un modèle de calcul flot de données reconfigurable

Dataflow Models of Computation (MoCs) are widely used in embedded systems, including multimedia processing, digital signal processing, telecommunications, and automatic control. In a dataflow MoC, an application is specified as a graph of actors connected by FIFO channels. One of the first and most popular dataflow MoCs, Synchronous Dataflow (SDF), provides static analyses to guarantee boundedness and liveness, which are key properties for embedded systems. However, SDF and most of its variants lacks the capability to express the dynamism needed by modern streaming applications. In particular, the applications mentioned above have a strong need for reconfigurability to accommodate changes in the input data, the control objectives, or the environment. We address this need by proposing a new MoC called Reconfigurable Dataflow (RDF). RDF extends SDF with transformation rules that specify how and when the topology and actors of the graph may be reconfigured. Starting from an initial RDF graph and a set of transformation rules, an arbitrary number of new RDF graphs can be generated at runtime. A key feature of RDF is that it can be statically analyzed to guarantee that all possible graphs generated at runtime will be consistent and live. We introduce the RDF MoC, describe its associated static analyses, and present its implementation and some experimental results.Les modèles de calcul (MoCs) flot de données synchrones sont très utilisés dans les systèmes embarqués et les applications multimédia, de traitement du signal, de télécommunication et de contrôle automatique. Dans ce style de modèle, une application est spécifiée par un graphe d’acteurs connectés par des liens FIFO de communication. Un des MoCs les plus connus, SDF (pour Synchronous Dataflow), permet des analyses statiques qui garantissent l’exécution en mémoire bornée et l’absence d’interblocage, propriétés clés pour les systèmes embarqués. Néanmoins, SDF (et la plupart de ses variantes) ne permet pas d’exprimer la dynamicité requise par les applications embarquées modernes. En particulier, ces applications ont souvent besoin de se reconfigurer pour s’adapter aux changements (par ex., de débit ou de qualité) du flot d’entrée, des objectifs de contrôle ou de l’environnement. Afin de répondre à ce besoin, nous proposons RDF (pour Reconfigurable DataFlow) un MoC qui étend SDF avec des règles de transformations spécifiant comment la topologie du graphe flot de données peut être reconfiguré dynamiquement. En considérant un graphe SDF initial et un ensemble de règles de transformation, un nombre arbitraire de nouveaux graphes peuvent être produits. La principale qualité de RDF est qu’il peut être analysé statiquement pour garantir que tous les graphes générés dynamiquement s’exécuteront en mémoire bornée et sans interblocage. Nous présentons le modèle RDF, les analyses statiques associées, sa mise en oeuvre et quelques expérimentations

RDF: A Reconfigurable Dataflow Model of Computation

International audienceDataflow Models of Computation (MoCs) are widely used in embedded systems, including multimedia processing, digital signal processing, telecommunications, and automatic control. In a dataflow MoC, an application is specified as a graph of actors connected by FIFO channels. One of the first and most popular dataflow MoCs, Synchronous Dataflow (SDF), provides static analyses to guarantee boundedness and liveness, which are key properties for embedded systems. However, SDF and most of its variants lack the capability to express the dynamism needed by modern streaming applications. In particular, the applications mentioned above have a strong need for reconfigurability to accommodate changes in the input data, the control objectives, or the environment. We address this need by proposing a new MoC called Reconfigurable Dataflow (RDF). RDF extends SDF with transformation rules that specify how and when the topology and actors of the graph may be reconfigured. Starting from an initial RDF graph and a set of transformation rules, an arbitrary number of new RDF graphs can be generated at runtime. A key feature of RDF is that it can be statically analyzed to guarantee that all possible graphs generated at runtime will be consistent and live. We introduce the RDF MoC, describe its associated static analyses, and present its implementation and some experimental results

METSTOR: a GIS to look for potential storage zones in France

International audienceCommunication : http://minh.haduong.com/files/Bonijoly.ea-2008-METSTOR-GHGT9.pdf - Actes : http://web.mit.edu/ghgt9

METSTOR: A GIS to look for potential CO2 storage zones in France

International audienceThe METSTOR project offers a methodology to look for potentially interesting CO2 storage areas in France at the initial stage, before the "site selection" step. Our tool, embodied in a Geographic Information System, is based on an interactive map of CO2 storage capacities. Other relevant information layers are included. The geographic layers are complemented with a series of online technical notices. It seems to be the first open online GIS that offers policy makers, businesses and the public at large an integrated access to that necessary information. Our prototype, limited mainly to the Paris Basin, is released online at www.metstor.fr