SoftwareX最新文献

筛选
英文 中文
GEMM-ArchProfiler: A simulation framework for hardware-level profiling and performance analysis of General Matrix Multiplication in real CNN workloads on heterogeneous CPU architectures GEMM-ArchProfiler:一个模拟框架,用于在异构CPU架构上的真实CNN工作负载中进行通用矩阵乘法的硬件级分析和性能分析
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-28 DOI: 10.1016/j.softx.2025.102243
Binu Ayyappan , G. Santhosh Kumar
{"title":"GEMM-ArchProfiler: A simulation framework for hardware-level profiling and performance analysis of General Matrix Multiplication in real CNN workloads on heterogeneous CPU architectures","authors":"Binu Ayyappan ,&nbsp;G. Santhosh Kumar","doi":"10.1016/j.softx.2025.102243","DOIUrl":"10.1016/j.softx.2025.102243","url":null,"abstract":"<div><div>In this paper, the authors present GEMM-ArchProfiler, a simulation framework for evaluating General Matrix Multiplication performance in convolutional neural networks. Targeted at resource-constrained edge and IoT systems, which rely on CPU-based architectures, the framework addresses hardware limitations through optimized workload profiling. Powered by the gem5 simulator, GEMM-ArchProfiler provides insights into memory usage, cache behavior, execution latency, and energy consumption. It integrates customized Darknet libraries to simulate realistic CNN workloads and includes a user-friendly CPU configuration mechanism and event analysis script. This tool bridges workload analysis and deployment, aiding efficient AI implementation on diverse CPU architectures.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102243"},"PeriodicalIF":2.4,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Vulnerable Neighborhood Explorer (VNE): An Open-Source Visual Analytics Tool for Exploring Social Vulnerability to Disasters across Different Neighborhoods 脆弱社区浏览器(VNE):一个开源的可视化分析工具,用于探索不同社区的社会脆弱性
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-28 DOI: 10.1016/j.softx.2025.102233
Su Yeon Han , Jooyoung Yoo , Alexander Michels , Jeon-Young Kang , Shaowen Wang , Joon-Seok Kim
{"title":"Vulnerable Neighborhood Explorer (VNE): An Open-Source Visual Analytics Tool for Exploring Social Vulnerability to Disasters across Different Neighborhoods","authors":"Su Yeon Han ,&nbsp;Jooyoung Yoo ,&nbsp;Alexander Michels ,&nbsp;Jeon-Young Kang ,&nbsp;Shaowen Wang ,&nbsp;Joon-Seok Kim","doi":"10.1016/j.softx.2025.102233","DOIUrl":"10.1016/j.softx.2025.102233","url":null,"abstract":"<div><div>We developed the Vulnerable Neighborhood Explorer (VNE), a geovisual analytics tool that helps decision-makers and researchers identify disaster-prone neighborhoods using socioeconomic and demographic data. By creating neighborhood boundaries from user-provided data, VNE enables analysis of disparities in disaster impacts (e.g., casualties, injuries, infections) and their socioeconomic drivers. It employs clustering algorithms and a dynamic interface with Coordinated and Multiple Views (CMV), linking maps and charts interactively. Features like cross-filtering and brushing instantly update visualizations, allowing seamless exploration of vulnerable neighborhoods and their population characteristics in specific disaster contexts.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102233"},"PeriodicalIF":2.4,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Rational-RC: A Python package for probabilistic life-cycle deterioration modelling of reinforced concrete structures Rational-RC:用于钢筋混凝土结构的概率寿命周期退化建模的Python包
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-26 DOI: 10.1016/j.softx.2025.102238
Gang Li , Jim Zacaruk , Moh Boulfiza
{"title":"Rational-RC: A Python package for probabilistic life-cycle deterioration modelling of reinforced concrete structures","authors":"Gang Li ,&nbsp;Jim Zacaruk ,&nbsp;Moh Boulfiza","doi":"10.1016/j.softx.2025.102238","DOIUrl":"10.1016/j.softx.2025.102238","url":null,"abstract":"<div><div>Maintaining the durability of reinforced concrete (RC) structures is crucial for sustainable infrastructure management. Rational-RC is a Python package that provides a probabilistic framework for modelling the life-cycle deterioration of RC structures. Designed with a modular, object-oriented architecture, it enables flexible integration of key deterioration processes, including membrane degradation, chloride ingress, carbonation, corrosion, and cracking within a unified limit-state reliability framework. Using site-specific field data, users can calibrate deterioration models to generate staged probabilities of failure, informing condition-based maintenance strategies that optimize costs and extend service life. The framework can be extended to interact with structural models, and scaled for simulation at both the element and network levels. Its visualization tools and extensible design make it a powerful tool for researchers and practitioners aiming to tackle the challenges of aging infrastructure with advanced computational approaches.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102238"},"PeriodicalIF":2.4,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
MCSim: A Multi-access Edge Computing Mobile CrowdSensing simulator MCSim:多接入边缘计算移动人群感知模拟器
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-26 DOI: 10.1016/j.softx.2025.102229
Dimitri Belli, Paolo Barsocchi, Antonino Crivello, Davide La Rosa, Michele Girolami
{"title":"MCSim: A Multi-access Edge Computing Mobile CrowdSensing simulator","authors":"Dimitri Belli,&nbsp;Paolo Barsocchi,&nbsp;Antonino Crivello,&nbsp;Davide La Rosa,&nbsp;Michele Girolami","doi":"10.1016/j.softx.2025.102229","DOIUrl":"10.1016/j.softx.2025.102229","url":null,"abstract":"<div><div>This paper introduces MCSim, a modular and extensible simulator designed to support the planning and evaluation of Mobile CrowdSensing (MCS) campaigns in urban environments. MCSim integrates a useful approximation of urban mobility patterns based on real-world street networks, as well as the simulation of task execution effectiveness within configurable data transmission ranges. Unlike other simulators, MCSim is built to accommodate future extensions, such as edge/fog computing architectures. The current version of the software offers a user-friendly interface, customizable configuration options, and robust output analysis. By combining realistic mobility modeling, configurable task logic, and architectural flexibility, MCSim provides researchers and practitioners with a powerful tool for optimizing MCS strategies while minimizing deployment costs and risks.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102229"},"PeriodicalIF":2.4,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
TensorConvolutionPlus: A python package for distribution system flexibility area estimation TensorConvolutionPlus:一个用于配电系统灵活性面积估计的python包
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-26 DOI: 10.1016/j.softx.2025.102241
Demetris Chrysostomou, José Luis Rueda Torres, Jochen Lorenz Cremer
{"title":"TensorConvolutionPlus: A python package for distribution system flexibility area estimation","authors":"Demetris Chrysostomou,&nbsp;José Luis Rueda Torres,&nbsp;Jochen Lorenz Cremer","doi":"10.1016/j.softx.2025.102241","DOIUrl":"10.1016/j.softx.2025.102241","url":null,"abstract":"<div><div>Power system operators need new, efficient operational tools to use the flexibility of distributed resources and deal with the challenges of highly uncertain and variable power systems. Transmission system operators can consider the available flexibility in distribution systems (DSs) without breaching the DS constraints through flexibility areas. However, there is an absence of open-source packages for flexibility area estimation. This paper introduces TensorConvolutionPlus, a user-friendly Python-based package for flexibility area estimation. The main features of TensorConvolutionPlus include estimating flexibility areas using the TensorConvolution+ algorithm, the power flow-based algorithm, an exhaustive PF-based algorithm, and an optimal power flow-based algorithm. Additional features include adapting flexibility area estimations from different operating conditions and including flexibility service providers offering discrete setpoints of flexibility. The TensorConvolutionPlus package facilitates a broader adaptation of flexibility estimation algorithms by system operators and power system researchers.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102241"},"PeriodicalIF":2.4,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DEXi Suite: DEXi decision modelling software DEXi Suite: DEXi决策建模软件
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-25 DOI: 10.1016/j.softx.2025.102240
Marko Bohanec
{"title":"DEXi Suite: DEXi decision modelling software","authors":"Marko Bohanec","doi":"10.1016/j.softx.2025.102240","DOIUrl":"10.1016/j.softx.2025.102240","url":null,"abstract":"<div><div>DEX (Decision EXpert) is a qualitative multi-criteria decision modelling method, and DEXi is software that supports the development of DEX models and their use for the evaluation and analysis of decision alternatives. We present DEXi Suite, a new generation of DEXi software, aimed at replacing the reliable and trusted, but dated, DEXi Classic software. DEXi Suite has been designed to employ a more modern and flexible software architecture and support extended functionality, while still remaining user-friendly and free to use. Currently, DEXi Suite consists of a DEXi modelling class library (DEXiLibrary), interactive desktop model editing and decision analysis software (DEXiWin) and a command-line evaluator (DEXiEval).</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102240"},"PeriodicalIF":2.4,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DMCpy: A powder and single crystal neutron diffraction software for the DMC diffractometer DMCpy:用于DMC衍射仪的粉末和单晶中子衍射软件
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-25 DOI: 10.1016/j.softx.2025.102237
Jakob Lass , Samuel Harrison Moody , Øystein Slagtern Fjellvåg
{"title":"DMCpy: A powder and single crystal neutron diffraction software for the DMC diffractometer","authors":"Jakob Lass ,&nbsp;Samuel Harrison Moody ,&nbsp;Øystein Slagtern Fjellvåg","doi":"10.1016/j.softx.2025.102237","DOIUrl":"10.1016/j.softx.2025.102237","url":null,"abstract":"<div><div>The recently upgraded DMC diffractometer at SINQ, Paul Scherrer Institute, Switzerland, equipped with a state-of-the-art 2D <span><math><msup><mrow></mrow><mrow><mn>3</mn></mrow></msup></math></span>He detector, enables high-resolution neutron diffraction experiments optimized for both powder and single-crystal studies. To address the increased complexity and volume of data produced by this instrument, we developed <span>DMCPy</span>, a Python-based software library tailored specifically to enable data analysis for DMC. <span>DMCPy</span> facilitates seamless data reduction and visualization, supporting conversion to reciprocal space, normalization, and masking of detector artifacts. Its modular architecture integrates tools for analyzing both powder diffraction patterns and single-crystal datasets, including advanced visualization features like 3D reciprocal space mapping and interactive scan inspection. By streamlining workflows and enhancing data interpretation, <span>DMCPy</span> empowers researchers to unlock the full potential of the DMC instrument for probing nuclear and magnetic structures in condensed matter systems.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102237"},"PeriodicalIF":2.4,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Pantera: A PIC-MCC-DSMC software for the simulation of rarefied gases and plasmas Pantera:用于模拟稀薄气体和等离子体的pic - mc - dsmc软件
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-25 DOI: 10.1016/j.softx.2025.102244
P. Parodi , S. Boccelli , F. Bariselli , T.E. Magin
{"title":"Pantera: A PIC-MCC-DSMC software for the simulation of rarefied gases and plasmas","authors":"P. Parodi ,&nbsp;S. Boccelli ,&nbsp;F. Bariselli ,&nbsp;T.E. Magin","doi":"10.1016/j.softx.2025.102244","DOIUrl":"10.1016/j.softx.2025.102244","url":null,"abstract":"<div><div>We present <span>Pantera</span>, an open-source, parallel, particle-based code for the simulation of rarefied gases and plasmas. The code uses the Particle-in-Cell (PIC) method for the solution of ionized flows in the electrostatic approximation, coupled to the Direct Simulation Monte Carlo (DSMC) method for particle–particle interactions, and Monte Carlo Collisions (MCC) technique for the interaction of particles with a fixed background. It uses unstructured grids, which allows for the representation of complex geometries. Various models are available for elastic collisions, reactions, and gas–surface interaction. Semi- and fully-implicit, energy-conserving PIC schemes are available, as well as a Boltzmann-fluid model for electrons, to improve numerical stability and speed up the simulations. The code is designed to be easily understandable and extensible to include new models and algorithms for aerospace applications and beyond.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102244"},"PeriodicalIF":2.4,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
SDSL-Mobile: Enabling space-efficient data structures for mobile applications SDSL-Mobile:为移动应用程序启用空间高效的数据结构
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-25 DOI: 10.1016/j.softx.2025.102234
Alexander Barquero , Anisha Wadhwani , Tyler Pencinger , Aaron Hong , Jaime Ruiz , Mattia Prosperi , Christina Boucher
{"title":"SDSL-Mobile: Enabling space-efficient data structures for mobile applications","authors":"Alexander Barquero ,&nbsp;Anisha Wadhwani ,&nbsp;Tyler Pencinger ,&nbsp;Aaron Hong ,&nbsp;Jaime Ruiz ,&nbsp;Mattia Prosperi ,&nbsp;Christina Boucher","doi":"10.1016/j.softx.2025.102234","DOIUrl":"10.1016/j.softx.2025.102234","url":null,"abstract":"<div><div>This paper presents the process and results of porting the Succinct Data Structure Library 2.0 (SDSL-lite), a robust and well-established open-source C++11 library, to Android platforms. The resulting library, called SDSL-Mobile, implements space-efficient data structures, including wavelet trees, compressed suffix arrays, and bit vectors, which are essential for handling large datasets in domains such as bioinformatics and information retrieval. Although originally designed for desktop environments, the library is extended to Android using the Android Native Development Kit (NDK) to enable integration into mobile platforms. Functionality is evaluated by implementing wavelet forests within an Android application, and performance is compared against a desktop implementation. The results demonstrate the feasibility of deploying succinct data structures on mobile devices, highlighting new possibilities for advanced data processing in resource-constrained environments.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102234"},"PeriodicalIF":2.4,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
TomoSAM: A 3D Slicer extension using SAM for tomography segmentation TomoSAM:使用SAM进行断层扫描分割的3D切片器扩展
IF 2.4 4区 计算机科学
SoftwareX Pub Date : 2025-06-24 DOI: 10.1016/j.softx.2025.102218
Federico Semeraro , Alexandre M. Quintart , Sergio Fraile Izquierdo , Joseph C. Ferguson
{"title":"TomoSAM: A 3D Slicer extension using SAM for tomography segmentation","authors":"Federico Semeraro ,&nbsp;Alexandre M. Quintart ,&nbsp;Sergio Fraile Izquierdo ,&nbsp;Joseph C. Ferguson","doi":"10.1016/j.softx.2025.102218","DOIUrl":"10.1016/j.softx.2025.102218","url":null,"abstract":"<div><div>TomoSAM has been developed to integrate the cutting-edge Segment Anything Model (SAM) into 3D Slicer, a highly capable software platform used for 3D image processing and visualization. SAM is a promptable deep learning model that is able to identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process. The source code associated with this article can be found at <span><span>https://github.com/fsemerar/SlicerTomoSAM</span><svg><path></path></svg></span> (see detailed code metadata).</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102218"},"PeriodicalIF":2.4,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144365651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信