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International Conference on Computing and Big Data (ICCBD)

作者： Cabutto, Tyler A. Heeney, Sean P. Ault, Shaun V. Mao, Guifen Wang, Jin Valdosta State Univ Dept Comp Sci Valdosta GA 31698 USA Valdosta State Univ Dept Math Valdosta GA USA

ISBN: (纸本)9781450365406

The paper reviews what the julia programming language is and its staying power relative to other popular programming languages. The following focuses on two popular programming languages (C programming and Python programming) to obtain a deeper understanding of what julia derives from them, how julia deviates from them, and what julia leverages to be a more reasonable choice for performance.

关键词： julia programming language C programming language Python programming language FORTRAN

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Experiment in Parallel Computing for the julia programming language

Experiment in Parallel Computing for the Julia Programming L...

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作者： Rui Song Xumin Song Yasheng Zhang Yanni Ma Space Engineering University

julia language is a free developing scripting language under the MIT license. Its goal is to case the difficulty of parallel programming. Based on the language mechanisms of julia, we constructed a use case of computing the average running-time between every two bus stops. And then, we exampled the julia programming framework and the code refining steps. julia language supports both multi-cores/CPUs parallel programming mode. To full use all the computing resources, we developed some experiments on new policies about how to improve the computing *** show that managing processors in parallel computing model consume working time, but with the increasing of problem size, this impact can be gradually ignored, and gaining nearly linear speedups.

关键词： Parallel Computing julia programming language Program optimization Performance analysis

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Development of Algorithmic and Software Support for Symbolic Computations in Problems of Constructing Controlled Compartmental Models of Dynamic Systems

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programming AND COMPUTER SOFTWARE 2025年第1期51卷 21-31页

作者： Petrov, A. A. Druzhinina, O. V. Masina, O. N. Demidova, A. V. Bunin Yelets State Univ Yelets 399770 Lipetsk Russia Russian Acad Sci Fed Res Ctr Comp Sci & Control Moscow 119333 Russia Peoples Friendship Univ Russia Moscow 117198 Russia

The analysis of epidemic spreading processes and the development of the corresponding algorithmic and software support for their mathematical modeling are important areas of research. The purpose of this work is to develop tools for symbolic computations in problems of constructing controlled compartmental models of dynamic systems. As a programming language, julia is used in combination with scientific computing libraries. A software package for compartmental modeling based on schemes of inter-compartment interactions is developed. Several controlled compartmental models-SIRU, SEIRU, and SIDARTHEU-are constructed and investigated. Control is implemented in the form of additional rules with variable transition rates. The developed software complex implements a domain-specific language for compartmental model construction based on interaction schemes. A simulation algorithm for controlled compartmental models is proposed. Computational experiments on controlled simulation of epidemic spreading are carried out, and the trajectory dynamics of the simulation models and corresponding differential models is analyzed. The results can be useful in modeling epidemiological, ecological, physicochemical, and other processes with one-step interactions.

关键词： controlled compartmental models dynamic systems computer algebra compartmental simulation algorithm julia programming language symbolic computing software

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HOPE: Holistic Optimization Program for Electricity

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SOFTWAREX 2025年 29卷

作者： Wang, Shen Song, Ziying Mehrtash, Mahdi Hobbs, Benjamin F. Johns Hopkins Univ Ralph OConnor Sustainable Energy Inst Baltimore MD 21218 USA MIT Ctr Energy & Environm Policy Res Cambridge MA 02139 USA Univ Calif San Diego Dept Mech & Aerosp Engn San Diego CA 92093 USA Univ Nevada Dept Elect & Biomed Engn Reno NV 89557 USA

In this paper, we present a novel open-source electricity systems optimization tool, the Holistic Optimization Program for Electricity (HOPE), to assess emerging generation technology, inform policy design, and support planning. With a highly transparent, interpretable, and compact model design, HOPE easily allows user access and modification, serving its main goal to benefit users beyond engineer communities and facilitate collaboration across the science-policy boundary. By activating different modes, the current version of HOPE (v1.0) offers flexibility in serving as either a Generation and Transmission Expansion Planning tool (GTEP) or a Production Cost Modelling tool (PCM). It includes modelling features such as long-term resource investments, short-term system operations, and a detailed representation of policies across various levels of regulated institutions. This paper outlines the building blocks of the model and its software structure. Case study results from using HOPE for the state of Maryland as well as the Pennsylvania-New Jersey-Maryland (PJM) footprint are also provided.

关键词： Power system planning Capacity expansion planning Production cost model Open-source software Power system optimization julia programming language

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***: A julia package for electronic structure calculation using density functional theory and plane wave basis

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COMPUTER PHYSICS COMMUNICATIONS 2020年 256卷 107372-107372页

作者： Fathurrahman, Fadjar Agusta, Mohammad Kemal Saputro, Adhitya Gandaryus Dipojono, Hermawan Kresno Bandung Inst Technol Dept Engn Phys Java Indonesia Bandung Inst Technol Res Ctr Nanosci & Nanotechnol Java Indonesia

We describe the implementation of ***, a package for electronic structure calculations written in julia programming language using plane wave basis set and pseudopotentials. In this package, a typical Kohn-Sham density functional theory (KSDFT) is divided into three steps: initializing the molecular or crystalline structure, constructing the Kohn-Sham Hamiltonian, and solving the Kohn-Sham problem using self-consistent field (SCF) calculation. To facilitate various tasks involved in these steps, we provide several custom data types which are transparent and easy to be modified. Basic operations such as wave function orthogonalization, action of kinetic and potential operators to wave functions and iterative diagonalization of Hamiltonian have been implemented in pure julia. Several algorithms to solve the Kohn-Sham problems such as self-consistent field and direct energy minimization have also been implemented in ***. To assess the validity of our implementation, we present the results of total energy calculations against the well-established ABINIT package. We also show how one can use *** to write a simple self-consistent field implementation. Program summary Program Title: *** CPC Library link to program files: http://***/10.17632/b87xzmzm2z.1 Licensing provisions: GPL-v2 programming language: julia Nature of problem: Electronic structure of interacting electrons in material Solution method: Kohn-Sham density functional theory, using plane wave basis set and pseudopotentials Additional comments including restrictions and unusual features: Due to the precompilation step, the program may appear to be slow at the first call. Parallelization is not yet considered. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Density functional theory Pseudopotential plane wave method julia programming language

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A unified efficient implementation of trust-region type algorithms for unconstrained optimization

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INFOR 2020年第2期58卷 290-309页

作者： Dussault, Jean-Pierre Univ Sherbrooke Dept Informat Sherbrooke PQ J1K 2R1 Canada

Adaptive cubic regularization (ARC) and trust-region (TR) methods use modified linear systems to compute their steps. The modified systems consist in adding some multiple of the identity matrix (or a well-chosen positive definite matrix) to the Hessian to obtain a sufficiently positive definite linear system, the so called shifted system. This type of system was first proposed by Levenberg and Marquardt. Some trial and error is often involved to obtain a specified value for this shift parameter. We provide an efficient unified implementation to track the shift parameter;our implementation encompasses many ARC and TR variants.

关键词： Nonlinear optimization unconstrained optimization trust-region algorithms adaptive cubic regularization methods julia programming language

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Effective computations of the Atiyah-Bott formula

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JOURNAL OF SYMBOLIC COMPUTATION 2022年第0期112卷 164-181页

作者： Muratore, Giosue Schneider, Csaba Univ Fed Minas Gerais Dept Math Belo Horizonte MG Brazil

We present an implementation of the Atiyah-Bott residue formula for M0,m(Pn, d). We use this implementation to compute a large number of Gromov-Witten invariants of genus 0, including intersection numbers of rational curves on general complete intersections. We also compute some numbers of rational contact curves satisfying suitable Schubert conditions. Our computations confirm known predictions made by Mirror Symmetry. The code we developed for these problems is publicly available and can also be used for other types of computations. (c) 2022 Elsevier Ltd. All rights reserved.

关键词： Contact Torus action Bott formula Enumeration SageMath julia programming language

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A Note on julia and MPI, with Code Examples

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COMPUTATIONAL ECONOMICS 2016年第3期48卷 535-546页

作者： Creel, Michael Univ Autonoma Barcelona Barcelona Grad Sch Econ Barcelona Spain MOVE Barcelona Spain

This note explains how MPI may be used with the julia programming language. An example of a simple Monte Carlo study is presented, with code. The code is intended to serve as a general purpose template for more relevant applications. A second example shows how the template code may be adapted to perform a Monte Carlo study of the properties of an approximate Bayesian computing estimator of actual research interest. All of the code is available at https://***/mcreel/juliaMPIMonteCarlo.

关键词： julia programming language Message passing interface Monte Carlo Approximate Bayesian computing

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Revisiting the Need for Conventional Safety Measurements in Modern Power Grids 34

Revisiting the Need for Conventional Safety Measurements in ...

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34th Australasian Universities Power Engineering Conference

作者： Pourazad, Hamed Braslaysky, Julio H. Seron, Maria M. Univ Newcastle Sch Engn Newcastle NSW Australia CSIRO Energy Syst Canberra ACT Australia

ISBN: (纸本)9798350377958;9798350377941

The growing adoption of Inverter-Based Resources (IBRs) in power grids has enabled the integration of renewable energy sources as viable alternatives to fossil-fuel-based thermal generators. Historically, conventional power grids have relied on synchronous generators, with safety indicators such as the Rate of Change of Frequency (RoCoF) being essential for handling reactions to disturbances and faults. However, due to the fundamental differences in the operation of inverters, the utilisation of such safety indicators can yield unintended and adverse outcomes, potentially compromising the reliability of the network. This paper investigates the impact of integrating inverter-based resources in the grid and examines the applicability of RoCoF as a safety indicator in modern power networks dominated by inverter-based generation. Through detailed simulations, we explore the behaviour of the grid during fault conditions and the subsequent frequency response of inverters. Our results demonstrate that, despite experiencing very high RoCoF values at the onset and clearance of faults, inverters can successfully maintain frequency synchronisation, even when inverter-based generation forms the majority of the grid's supply. These findings suggest that traditional safety measures, such as the automatic disconnection of inverters based on high RoCoF values, may no longer be appropriate.

关键词： Renewable energy integration Renewable power generation RoCoF System strength Safety measurements julia programming language

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Performance of julia for High Energy Physics Analyses

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Computing and Software for Big Science 2021年第1期5卷 1-11页

作者： Stanitzki, Marcel Strube, Jan DESY Notkestrasse 85 Hamburg 22607 Germany University of Oregon 1371 E 13th Avenue Eugene 97403 OR United States Pacific Northwest National Laboratory 902 Battelle Blvd Richland 99352 WA United States

We argue that the julia programming language is a compelling alternative to implementations in Python and C++ for common data analysis workflows in high energy physics. We compare the speed of implementations of different workflows in julia with those in Python and C++. Our studies show that the julia implementations are competitive for tasks that are dominated by computational load rather than data access. For work that is dominated by data access, we demonstrate an application with concurrent file reading and parallel data processing. © 2021, Springer Nature Switzerland AG.

关键词： Data analysis High energy physics julia programming language Multithreading

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