Sébastien Limet

FlowVR: A Middleware for Large Scale Virtual Reality Applications

This paper introduces FlowVR, a middleware dedicated to virtual reality applications distributed on clusters or grid environments. FlowVR supports coupling of heterogeneous parallel codes and is component oriented to favor code reuse. While classical communication paradigms focus on either a synchronous approach (FIFO channels) or an asynchronous one (sampling), FlowVR enables a large range of intermediate policies to better balance the application performance between levels of details, latencies and refresh rates.

Interactive Molecular Dynamics: Scaling up to Large Systems☆

Combining molecular dynamics simulations with user interaction would have various applications in both education and research. By enabling interactivity the scientist will be able to visualize the experiment in real time and drive the simulation to a desired state more easily. However, interacting with systems of interesting size requires significant computing resources due to the complexity of the simulation. In this paper, we propose an approach to combine a classical parallel molecular dynamics simulator, Gromacs, to a 3D virtual reality environment allowing to steer the simulation through external user forces applied with an haptic device to a selection of atoms. We specifically focused on minimizing the intrusion in the simulator code, on efficient parallel data extraction and filtering to transfer only the necessary data to the visualization environment, and on a controlled asynchronism between various components to improve interactivity. We managed to steer molecular systems of 1.7M atoms at about 25 Hz using 384 CPU cores. This framework allowed us to study a concrete scientific problem by testing one hypothesis of the transport of an iron complex from the exterior of the bacteria to the periplasmic space through the FepA membrane protein.

Parallel Computing Flow Accumulation in Large Digital Elevation Models

This paper describes a new fast and scalable parallel algorithm to compute global flow accumulation for automatic drainage network extraction in large digital elevation models (DEM for short). Our method uses the D8 model to compute the flow directions for all pixels in the DEM (except NODATA and oceans). A parallel spanning tree algorithm is proposed to compute hierarchical catchment basins to model the flow of water from a sink (local minima) moving on DEM to its outlet (ocean, NODATA, or border of DEM). And finally, based on local flow accumulation and the hierarchical trees between sinks, we determinate entirely the global flow accumulation. From that, the drainage networks of DEM can be extracted. Our method does not need any preprocessing like stream burning on the initial DEM and tends to make the most of incomplete DEMs. Our algorithms are entirely parallel. Efficiency and scalability have been tested on different large DEMs.

Proving Properties of Term Rewrite Systems via Logic Programs

We present a general translation of term rewrite systems (TRS) to logic programs such that basic rewriting derivations become logic deductions. Certain TRS result in so-called cs-programs, which were originally studied in the context of constraint systems and tree tuple languages. By applying decidability and computability results of cs-programs we obtain new classes of TRS that have nice properties like decidability of unification, regular sets of descendants or finite representations of R-unifiers. Our findings generalize former results in the field of term rewriting.

A New Result about the Decidability of the Existential One-Step Rewriting Theory

We give a decision procedure for the whole existential fragment of one-step rewriting first-order theory, in the case where rewrite systems are linear, non left-left-overlapping (i.e. without critical pairs), and non Ɛ-left-right-overlapping (i.e. no left-hand-side overlaps on top with the right-hand-side of the same rewrite rule). The procedure is defined by means of tree-tuple synchronized grammars.

Manipulating Tree Tuple Languages by Transforming Logic Programs.

Abstract We introduce inductive definitions over language expressions as a framework for specifying tree tuple languages. Inductive definitions and their sub-classes correspond naturally to classes of logic programs, and operations on tree tuple languages correspond to the transformation of logic programs. We present an algorithm based on unfolding and definition introduction that is able to deal with several classes of tuple languages in a uniform way. Termination proofs for clause classes translate directly to closure properties of tuple languages, leading to new decidability and computability results for the latter.

Solving Disequations Modulo Some Class of Rewrite Systems

This paper gives a procedure for solving disequations modulo equational theories, and to decide existence of solutions. For this, we assume that the equational theory is specified by a confluent and constructor-based rewrite system, and that four additional restrictions are satisfied. The procedure represents the possibly infinite set of solutions thanks to a grammar, and decides existence of solutions thanks to an emptiness test. As a consequence, checking whether a linear equality is an inductive theorem is decidable, if assuming moreover sufficient completeness.

High‐performance computing: to boldly go where no human has gone before

Computing and computational science are well on their way to enter into the exascale era while High Performance Computing (HPC) is now present in many spheres and domains of modern society. New technologies such as cloud computing, big data, and connected objects open many perspectives and possibilities that were unattainable until now. These are high times for computing and for HPC in particular. The High Performance Computing \& Simulation conference aims to bring together researchers working on various aspects of HPC, their design and use, and their applications. As has been the conference tradition, selected extended papers of HPCS 2012 are presented in this special issue. These should be interesting contributions that supplement the current state-of-the-art research in HPC. To relate these works and highlight their value, in this article, we briefly trace back the history of HPC, sketch the state of the present research and development in the field, and project some of the challenges and future trends anticipated.

Parallel computing of catchment basins in large digital elevation model

This paper presents a fast and flexible parallel implementation to compute catchment basins in the large digital elevation models (DEM for short). This algorithm aims at using all the specific properties of the problem to optimize local computations and to avoid useless communications or synchronizations. The algorithm has been implemented in MPI and the first benchmarks show the scalability of the method.

Tree Tuple Languages from the Logic Programming Point of View

We introduce inductive definitions over language expressions as a framework for specifying tree tuple languages. Inductive definitions and their subclasses correspond naturally to classes of logic programs, and operations on tree tuple languages correspond to the transformation of logic programs. We present an algorithm based on unfolding and definition introduction that is able to deal with several classes of tuple languages in a uniform way. Termination proofs for clause classes translate directly to closure properties of tuple languages, leading to new decidability and computability results for the latter.