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Section: New Results

Other results

Chemical programming

Participants : Pascal Fradet [ contact person ] , Marnes Hoff.

The chemical reaction metaphor describes computation in terms of a chemical solution in which molecules (representing data) interact freely according to reaction rules (representing the program). Formally, chemical programs can be represented as associative-commutative rewritings (reactions) of multisets (chemical solutions). This model of computation is well-suited to the specification of complex computing infrastructures. In particular, the orderless interactions between elements that occur in large parallel or open systems as well as autonomicity (e.g. self-healing, self-protection, self-optimization, etc.) are naturally expressed as reaction rules.

In the context of the InterLink coordination action (see Section  8.3.5 ), we have written a review of recent advances concerning the chemical reaction model  [25] . This work presents several generalizations of the basic model (higher-order reactions, hybrid and infinite multisets) and current research directions. We have also described classical coordination mechanisms and parallel programming models (Linda, Petri Nets, Kahn Networks) in the same chemical setting  [24] . All these examples put forward the simplicity and expressivity of the chemical paradigm.

This work was conducted in collaboration with Jean-Pierre Banâtre and Yann Radenac from the Paris project team at Irisa .

A drawback of chemical languages is that their very high-level nature usually leads to very inefficient programs. We are currently looking at approaches to refine chemical programs to more efficient lower-level programs. Several research directions are promising: richer types and data structures, domain-specific languages or aspects describing separately implementation issues (such as the evaluation strategy or data representation).

This line of research is part of Marnes Hoff's PhD thesis and takes place within the AutoCHEM project (see Section  8.2.1 ).

Component-based modeling and reachability analysis of genetic networks

Participant : Gregor Goessler.

Genetic regulatory networks usually encompass a multitude of complex, interacting feedback loops. Being able to model and analyze their behavior is crucial for understanding the interactions between the proteins, and their functions. Genetic regulatory networks have been modeled as discrete transition systems by many approaches, benefiting from a large number of formal verification algorithms available for the analysis of discrete transition systems. However, most of these approaches face the problem of state space explosion, as even models of modest size (from a biological point of view) usually lead to large transition systems, due to a combinatorial blow-up of the number of states. This problem has been addressed with the component-based approach of  [59] — based on the mathematically well-founded formalism of qualitative simulation  [50] — where the discrete abstraction is constructed and analyzed modularly, allowing to deal with complex, high-dimensional systems.

We have further improved this technique by allowing for a more precise, conservative abstraction, and provided both correctness and completeness results  [32] .

Using the same approach, we are studying, in cooperation with H. de Jong ( Ibis project team) and G. Batt ( Contraintes project team), the definition of a symbolic representation of the network behavior as a compact exchange format between the Genetic Network Analyzer (GNA) developed in the Ibis project team, and the model cheker CADP developed by Vasy .

Control for data-parallel systems

Participant : Eric Rutten.

Data intensive computing is increasingly getting high importance in a wide range of scientific and engineering domains, like multi-media portable devices. Such systems manipulate large amounts of data; so high performance, scalability and throughput are important requirements. Reconfigurability is another interesting feature because it makes the systems flexible enough to be adapted to various environment and resource constraints. The Gaspard2 (http://www.lifl.fr/west/gaspard )development framework aims at proposing a solution to the design of data intensive applications in general, and high-performance embedded system-on-chip (SoCs) in particular.

We have proposed a synchronous model of Gaspard2   [19] , [12] , in order to bridge the gap between Gaspard2 and analysis and verification tools of the synchronous technology so that formal validation is favored  [22] . The automation of the transformations is implemented within an MDE framework  [26] . We extended Gaspard2 , by adding reactive control features based on finite state machines, and are integrating this extension in the synchronous model  [31] .

This work is conducted in cooperation with the DaRT project at UR Futurs in Lille.


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