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The aim of this paper is to propose the intermodal logistics Corridor Vc, relying on the European Union transport policy, which will be in the function of regional development. The main goal is to analyze a potential route of freight intermodal transport between the ports of Ploče and Brčko in order to popularize this intermodal line at the international level. Among the most important activities in achieving this goal is the integration in the Euro corridor system. This integration is of crucial importance for companies to successfully execute their supply chain processes both domestically and internationally. The paper is based on the analysis of the current socio-economic situation and the condition of the intermodal transport system in Bosnia and Herzegovina (BiH), as well as existing strategic studies and development plans. This paper sheds a light on the creation of a strong integrated intermodal freight transport network in BiH, that will be a quality alternative to other international intermodal flows from the aspect of shorter transport time, lower transport costs and more favorable ecological aspects of transportation.

With the growing datasets of current and next-generation HighEnergy and Nuclear Physics (HEP/NP) experiments, statistical analysis has become more computationally demanding. These increasing demands elicit improvements and modernizations in existing statistical analysis software. One way to address these issues is to improve parameter estimation performance and numeric stability using Automatic Differentiation (AD). AD’s computational efficiency and accuracy are superior to the preexisting numerical differentiation techniques, and it offers significant performance gains when calculating the derivatives of functions with a large number of inputs, making it particularly appealing for statistical models with many parameters. For such models, many HEP/NP experiments use RooFit, a toolkit for statistical modeling and fitting that is part of ROOT. In this paper, we report on the effort to support the AD of RooFit likelihood functions. Our approach is to extend RooFit with a tool that generates overheadfree C++ code for a full likelihood function built from RooFit functional models. Gradients are then generated using Clad, a compiler-based source-codetransformation AD tool, using this C++ code. We present our results from applying AD to the entire minimization pipeline and profile likelihood calculations of several RooFit and HistFactory models at the LHC-experiment scale. We show significant reductions in calculation time and memory usage for the minimization of such likelihood functions. We also elaborate on this approach’s current limitations and explain our plans for the future.

In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evaluate the derivative of a function specified by a computer program. AD exploits the fact that every computer program, no matter how complicated, executes a sequence of elementary arithmetic operations (addition, subtraction, multiplication, division, etc.), elementary functions (exp, log, sin, cos, etc.) and control flow statements. AD takes source code of a function as input and produces source code of the derived function. By applying the chain rule repeatedly to these operations, derivatives of arbitrary order can be computed automatically, accurately to working precision, and using at most a small constant factor more arithmetic operations than the original program. This paper presents AD techniques available in ROOT, supported by Cling, to produce derivatives of arbitrary C/C++ functions through implementing source code transformation and employing the chain rule of differential calculus in both forward mode and reverse mode. We explain its current integration for gradient computation in TFormula. We demonstrate the correctness and performance improvements in ROOT’s fitting algorithms.

C++ Modules, one of the new features of C++20, aim to fix the long-standing build scalability problems in the language. They provide an IOefficient, on-disk representation capable to reduce build times and peak memory usage. ROOT already employs the C++ modules technology in its dictionary system to improve performance and reduce the memory footprint. ROOT with C++ Modules was released as a technology preview in fall 2018, after intensive development during the previous few years. The current state is ready for production, however, there is still room for performance optimizations. In this talk, we show the road map for making this technology enabled by default in ROOT. We demonstrate a global module indexing optimization which allows reducing the memory footprint dramatically for many workflows. We will report user feedback on the migration to ROOT with C++ Modules.

The ROOT software framework is foundational for the HEP ecosystem, providing multiple capabilities such as I/O, a C++ interpreter, GUI, and math libraries. It uses object-oriented concepts and build-time components to layer between them. We believe that a new layering formalism will benefit the ROOT user community. We present the modularization strategy for ROOT which aims to build upon the existing source components, making available the dependencies and other metadata outside of the build system, and allow post-install additions on top of existing installation as well as in the ROOT runtime environment. Components can be grouped into packages and made available from repositories in order to provide a post-install step of missing packages. This feature implements a mechanism for the more comprehensive software ecosystem and makes it available even from a minimal ROOT installation. As part of this work, we have reduced inter-component dependencies in order to improve maintainability. The modularization effort draws inspiration from similar efforts in the Java, Python, and Swift ecosystems. Keeping aligned with modern C++, this strategy relies on forthcoming features such as C++ modules. We hope formalizing the component layer provides simpler ROOT installs, improves extensibility, and decreases the complexity of embedding ROOT in other ecosystems.

ROOT is a data analysis framework broadly used in and outside of High Energy Physics (HEP). Since HEP software frameworks always strive for performance improvements, ROOT was extended with experimental support of runtime C++ Modules. C++ Modules are designed to improve the performance of C++ code parsing. C++ Modules offers a promising way to improve ROOT’s runtime performance by saving the C++ header parsing time which happens during ROOT runtime. This paper presents the results and challenges of integrating C++ Modules into ROOT.

Collaboration in research is essential for saving time and money. The field of high-energy physics (HEP) is no different. The higher level of collaboration the stronger the community. The HEP field encourages organizing various events in format and size such as meetings, workshops and conferences. Making attending a HEP event easier leverages cooperation and dialogue and this is what makes Indico service defacto a community standard. The paper describes HEPCon, a cross-platform mobile application which collects all information available on Indico and makes it available on a portable device. It keeps most of the data locally which speeds up the interaction. HEP-Con uses a shared code base which allows easy multiplatform development and support. There are iOS and Android implementations available for free download. The project is based on C# and we use the Xamarin mobile app technology for building native iOS and Android apps. SQLite database is responsible for retrieving and storing conference data. The app can be used to preview data from past CHEP conferences but the tool is implemented generic enough to support other Indico events.

Foundational software libraries such as ROOT are under intense pressure to avoid software regression, including performance regressions. Continuous performance benchmarking, as a part of continuous integration and other code quality testing, is an industry best-practice to understand how the performance of a software product evolves. We present a framework, built from industry best practices and tools, to help to understand ROOT code performance and monitor the efficiency of the code for several processor architectures. It additionally allows historical performance measurements for ROOT I/O, vectorization and parallelization sub-systems.

The 23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP) took place in the National Palace of Culture, Sofia, Bulgaria from 9th to 13th of July 2018. 575 participants joined the plenary and the eight parallel sessions dedicated to: online computing; offline computing; distributed computing; data handling; software development; machine learning and physics analysis; clouds, virtualisation and containers; networks and facilities. The conference hosted 35 plenary presentations, 323 parallel presentations and 188 posters.

In this article we consider a critical thermodynamic system with the shape of a thin film confined between two parallel planes. It is assumed that the state of the system at a given temperature and external ordering field is described by order-parameter profiles, which minimize the one-dimensional counterpart of the standard ϕ4 Ginzburg–Landau Hamiltonian and meet the so-called Neumann – Neumann boundary conditions. We give analytic representation of the extremals of this variational problem in terms ofWeierstrass elliptic functions. Then, depending on the temperature and ordering field we determine the minimizers and obtain the phase diagram in the temperature-field plane.

The behaviour of the local and total susceptibilities of a fluid system bounded by different surfaces is studied in the framework of the Ginsburg-Landau Ising type model. The case of a plain geometry, Neumann-infinity boundary conditions under variations of the temperature and an external ordering field is considered. Exact analytic expressions for the order parameter, local and total susceptibilities in such a system are presented. They are used to analyse the phase behaviour of fluids confined in regions close to the bulk critical point of the respective infinite system.