Solving XCSP problems by using Gecode

Gecode is one of the most efficient libraries that can be used for constraint solving. However, using it requires dealing with C++ programming details. On the other hand several formats for representing constraint networks have been proposed. Among them, XCSP has been proposed as a format based on XML which allows us to represent constraints defined either extensionally or intensionally, permits global constraints and has been the standard format of the international competition of constraint satisfaction problems solvers. In this paper we present a plug-in for solving problems specified in XCSP by exploiting the Gecode solver. This is done by dynamically translating constraints into Gecode library calls, thus avoiding the need to interact with C++.Comment: 5 pages, http://ceur-ws.org/Vol-810 CILC 201

SUNNY-CP and the MiniZinc Challenge

In Constraint Programming (CP) a portfolio solver combines a variety of different constraint solvers for solving a given problem. This fairly recent approach enables to significantly boost the performance of single solvers, especially when multicore architectures are exploited. In this work we give a brief overview of the portfolio solver sunny-cp, and we discuss its performance in the MiniZinc Challenge---the annual international competition for CP solvers---where it won two gold medals in 2015 and 2016. Under consideration in Theory and Practice of Logic Programming (TPLP)Comment: Under consideration in Theory and Practice of Logic Programming (TPLP

A Multicore Tool for Constraint Solving

*** To appear in IJCAI 2015 proceedings *** In Constraint Programming (CP), a portfolio solver uses a variety of different solvers for solving a given Constraint Satisfaction / Optimization Problem. In this paper we introduce sunny-cp2: the first parallel CP portfolio solver that enables a dynamic, cooperative, and simultaneous execution of its solvers in a multicore setting. It incorporates state-of-the-art solvers, providing also a usable and configurable framework. Empirical results are very promising. sunny-cp2 can even outperform the performance of the oracle solver which always selects the best solver of the portfolio for a given problem

Dynamic Choreographies: Theory And Implementation

Programming distributed applications free from communication deadlocks and race conditions is complex. Preserving these properties when applications are updated at runtime is even harder. We present a choreographic approach for programming updatable, distributed applications. We define a choreography language, called Dynamic Interaction-Oriented Choreography (AIOC), that allows the programmer to specify, from a global viewpoint, which parts of the application can be updated. At runtime, these parts may be replaced by new AIOC fragments from outside the application. AIOC programs are compiled, generating code for each participant in a process-level language called Dynamic Process-Oriented Choreographies (APOC). We prove that APOC distributed applications generated from AIOC specifications are deadlock free and race free and that these properties hold also after any runtime update. We instantiate the theoretical model above into a programming framework called Adaptable Interaction-Oriented Choreographies in Jolie (AIOCJ) that comprises an integrated development environment, a compiler from an extension of AIOCs to distributed Jolie programs, and a runtime environment to support their execution.Comment: arXiv admin note: text overlap with arXiv:1407.097

Dynamic Choreographies - Safe Runtime Updates of Distributed Applications

Programming distributed applications free from communication deadlocks and races is complex. Preserving these properties when applications are updated at runtime is even harder. We present DIOC, a language for programming distributed applications that are free from deadlocks and races by construction. A DIOC program describes a whole distributed application as a unique entity (choreography). DIOC allows the programmer to specify which parts of the application can be updated. At runtime, these parts may be replaced by new DIOC fragments from outside the application. DIOC programs are compiled, generating code for each site, in a lower-level language called DPOC. We formalise both DIOC and DPOC semantics as labelled transition systems and prove the correctness of the compilation as a trace equivalence result. As corollaries, DPOC applications are free from communication deadlocks and races, even in presence of runtime updates.Comment: Technical Repor

Wormlike reverse micelles in lecithin/bile salt/water mixtures in oil

Knowing the ability of water and bile salts to promote the reverse wormlike micelle growth in lecithin/water or lecithin/bile salt mixtures in oil, this work was aimed at elucidating the association properties of the three solutes lecithin, water and the bile salt (BS) sodium deoxycholate in cyclohexane. By systematically changing the fraction of the two additives (i.e.: water and BS) we could identify a region at low additive/lecithin molar ratios where stable wormlike micelle dispersions were formed. Small angle X-ray scattering and oscillatory rheology measurements demonstrated that the ability of bile salt and water to transform the originally spherical lecithin reverse micelles into wormlike micelles and thereby impart to the sample viscoelastic properties is preserved in the three-solute mixture. The results suggest that reverse micelle including both bile salt and water are formed in this system. Reasonably the two primers interact with the same region of the lecithin headgroups and are complementary in altering the packing parameter of the amphiphile to values suitable for the formation of cylindrical aggregates

Chiral discrimination in helicity-preserving Fabry-Pérot cavities

We theoretically study circular dichroism of chiral molecules embedded inside a helicity-preserving Fabry-Pérot cavity. We find an increase of the intrinsic chiroptical response of the molecules by 2 orders of magnitude and report the first clear signature of chiral cavity polaritons upon entering the regime of strong light-matter coupling. We study a cavity design based on two dielectric photonic crystal mirrors acting, in a narrow frequency range, as efficient polarization cross-converters in transmission for one polarization and almost perfect reflectors for the other polarization. We show that a Pasteur medium hosted inside such a cavity can couple efficiently to both the outside of the cavity and to the helicity-preserving mode, inheriting an enhanced chiral character. We expect such a device to be useful in the future to design ultrasensitive chiral sensors for optics and stereochemistr

An Extensive Evaluation of Portfolio Approaches for Constraint Satisfaction Problems

In the context of Constraint Programming, a portfolio approach exploits the complementary strengths of a portfolio of different constraint solvers. The goal is to predict and run the best solver(s) of the portfolio for solving a new, unseen problem. In this work we reproduce, simulate, and evaluate the performance of different portfolio approaches on extensive benchmarks of Constraint Satisfaction Problems. Empirical results clearly show the benefits of portfolio solvers in terms of both solved instances and solving time

Dynamic optimization of provider-based scheduling for HPC workloads

The vast array of cloud providers present in today’s market proffer a suite of High-Performance Computing (HPC) services. However, these offerings are characterized by significant variations in execution times and cost structures. Consequently, selecting the optimal cloud provider and configuring the features of the chosen computing instance (e.g. virtual machines) proves to be a challenging task for users intending to execute HPC workloads. This paper introduces a novel component designed for effortless integration with existing HPC scheduling systems. This module’s primary function is to facilitate the selection of the most appropriate cloud provider for each distinct job, thereby empowering dynamic and adaptive cost-minimization strategies. Through the application of data augmentation techniques and the employment of Continuous Machine Learning, the system is endowed with the capability to operate efficiently with cloud providers that have not been previously utilized. Furthermore, it is capable of tracking the evolution of jobs over time. Our results show that this component can achieve consistent economic savings, based on the quality of the data used in the training phase