Journals in Performance of systems

BenchCouncil Transactions on Benchmarks, Standards and Evaluations

ISSN: 2772-4859

BenchCouncil Transactions on Benchmarks, Standards and Evaluations (TBench) is an open-access, multi-disciplinary journal dedicated to advancing the science and engineering of evaluation. We extend a warm invitation to researchers from diverse disciplines to submit their work, with a particular emphasis on interdisciplinary research. Whether the research pertains to computers, artificial intelligence (AI), medicine, education, finance, business, psychology, or other social disciplines, all relevant contributions are highly valued and welcomed.At TBench, we place great importance on the reproducibility of research. We strongly encourage authors to ensure that their articles are appropriately prepared for open-source or artifact evaluation prior to submission. Areas of interest include, but are not limited to:1. Evaluation theory and methodologyFormal specification of evaluation requirementsDevelopment of evaluation modelsDesign and implementation of evaluation systemsAnalysis of evaluation riskCost modeling for evaluationsAccuracy modeling for evaluationsEvaluation traceabilityIdentification and establishment of evaluation conditionsEquivalent evaluation conditionsDesign of experimentsStatistical analysis techniques for evaluationsMethodologies and techniques for eliminating confounding factors in evaluationsAnalytical modeling techniques and validation of modelsSimulation and emulation-based modeling techniques and validation of modelsDevelopment of methodologies, metrics, abstractions, and algorithms specifically tailored for evaluations2. The engineering of evaluation Benchmark design and implementationBenchmark traceability Establishing least equivalent evaluation conditionsIndex design, implementationScale design, implementationEvaluation standard design and implementationsEvaluation and benchmark practice Tools for evaluationsReal-world evaluation systemsTestbed3. Data setExplicit or implicit problem definition deduced from the data setDetailed descriptions of research or industry datasets, including the methods used to collect the data and technical analyses supporting the quality of the measurementsAnalyses or meta-analyses of existing dataSystems, technologies, and techniques that advance data sharing and reuse to support reproducible researchTools that generate large-scale data while preserving their original characteristicsEvaluating the rigor and quality of the experiments used to generate the data and the completeness of the data description4. BenchmarkingSummary and review of state-of-the-art and state-of-the-practiceSearching and summarizing industry best practiceEvaluation and optimization of industry practiceRetrospective of industry practiceCharacterizing and optimizing real-world applications and systemsEvaluations of state-of-the-art solutions in the real-world setting5. Measurement and testingWorkload characterizationInstrumentation, sampling, tracing, and profiling of large-scale, real-world applications and systemsCollection and analysis of measurement and testing data that yield new insightsMeasurement and testing-based modeling (e.g., workloads, scaling behavior, and assessment of performance bottlenecks)Methods and tools to monitor and visualize measurement and testing dataSystems and algorithms that build on measurement and testing-based findingsReappraisal of previous empirical measurements and measurement-based conclusionsReappraisal of previous empirical testing and testing-based conclusionsEditorial Board

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Journal of Computational Science

ISSN: 1877-7503
5 Year impact factor: 3.4
Impact factor: 3.1

Computational Science is a rapidly growing multi- and interdisciplinary field. It develops mathematical and computational models and uses advanced computing techniques to simulate these models, driven by data. Its overarching goal is to understand and solve complex problems. It has reached a level of predictive and interventional capability that now firmly complements the traditional pillars of experimentation and theory.The recent advances in experimental techniques have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data-driven modeling and simulation which is no longer feasible using traditional analytical approaches alone.This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods.Computational science typically unifies three distinct elements:• Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).The Journal of Computational Science aims to be an international platform to exchange novel research results in simulation-based science across all scientific disciplines. It publishes advanced innovative, interdisciplinary research where complex multi-scale, multi-domain problems in science and engineering are solved, integrating sophisticated numerical methods, computation, data, networks, and novel devices.The journal welcomes original, unpublished high quality contributions in the field of computational science at large, addressing one or more of the aforementioned elements.

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Journal of Parallel and Distributed Computing

ISSN: 0743-7315
5 Year impact factor: 3.4
Impact factor: 3.4

Researchers interested in submitting a special issue proposal should adhere to the submission guidelines.This international journal is directed to researchers, engineers, educators, managers, programmers, and users of computers who have particular interests in parallel processing and/or distributed computing.The Journal of Parallel and Distributed Computing publishes original research papers and timely review articles on the theory, design, evaluation, and use of parallel and/or distributed computing systems. The journal also features special issues on these topics; again covering the full range from the design to the use of our targeted systems.Research Areas Include:• Theory of parallel and distributed computing • Parallel algorithms and their implementation • Innovative computer architectures • Parallel programming • Applications, algorithms and platforms for accelerators • Cloud, edge and fog computing • Data-intensive platforms and applications • Parallel processing of graph and irregular applications • Parallel and distributed programming models • Software tools and environments for distributed systems • Algorithms and systems for Internet of Things • Performance analysis of parallel applications • Architecture for emerging technologies e.g., novel memory technologies, quantum computing • Application-specific architectures e.g., accelerator-based and reconfigurable architecture • Interconnection network, router and network interface architectureBenefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center

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Parallel Computing

ISSN: 0167-8191
5 Year impact factor: 1.3
Impact factor: 2

Systems & ApplicationsResearchers interested in submitting a special issue proposal should adhere to the Submission Guidelines.Parallel Computing is an international journal presenting the practical use of parallel computer systems, including high performance architecture, system software, programming systems and tools, and applications. Within this context the journal covers all aspects of high-end parallel computing from single homogeneous or heterogenous computing nodes to large-scale multi-node systems.Parallel Computing features original research work and review articles as well as novel or illustrative accounts of application experience with (and techniques for) the use of parallel computers. We also welcome studies reproducing prior publications that either confirm or disprove prior published results.Particular technical areas of interest include, but are not limited to:System software for parallel computer systems including programming languages (new languages as well as compilation techniques), operating systems (including middleware), and resource management (scheduling and load-balancing).Enabling software including debuggers, performance tools, and system and numeric libraries.General hardware (architecture) concepts, new technologies enabling the realization of such new concepts, and details of commercially available systemsSoftware engineering and productivity as it relates to parallel computingApplications (including scientific computing, deep learning, machine learning) or tool case studies demonstrating novel ways to achieve parallelismPerformance measurement results on state-of-the-art systemsApproaches to effectively utilize large-scale parallel computing including new algorithms or algorithm analysis with demonstrated relevance to real applications using existing or next generation parallel computer architectures.Parallel I/O systems both hardware and softwareNetworking technology for support of high-speed computing demonstrating the impact of high-speed computation on parallel applicationsBenefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center

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Performance Evaluation

ISSN: 0166-5316
5 Year impact factor: 1.1
Impact factor: 1

Performance Evaluation is a leading journal in the area of modeling, measurement, and evaluation of performance aspects of computing and communication systems. As such, it aims to present a balanced and complete view of the entire field of performance evaluation. The journal audience encompasses academics, industrial researchers, and professional figures such as performance engineers, network managers, and computer system designers.The journal solicits from its audience papers that focus on one or more of the following dimensions: Define new performance evaluation tools, including measurement and monitoring tools as well as modeling and analytic techniquesProvide new insights into the performance of computing and communication systemsPresent novel control and learning methods for performance managementIntroduce new application areas where performance evaluation tools and methods can play an important role Contributions to the journal often focus on theoretical, methodological, or applied aspects of:Resource allocation (e.g., routing and flow control, bandwidth allocation, load-balancing, deployment,...System tuning, sizing and optimal configurationSystem reliability and dependabilityEnergy efficiency and energy harvestingSystem architecture design and implementation Application areas of interest include, but are not limited to, the following:Computer and communication networks (e.g., software-defined, wireless, cognitive radio, ad-hoc, quantum,...Data centersCloud, IoT, edge, and cyber-physical systemsSocial networks, social media, metaverseAI-based servicesBig data and storage systemsBlockchain and distributed ledgersAutonomous and self-organizing systemsEmbedded systems Commonly featured performance evaluation methods and techniques include:Stochastic models (e.g., queueing theory, mean-field models, stochastic geometry,...Data-driven methods (e.g., AI/machine learning, inference, statistical analysis, ...)Scheduling and load balancing theorySimulation methodsGame theory and pricingMeasurement techniques (e.g. software and hardware monitors) and workload characterization Note that the above lists are not all inclusive or restrictive and submissions with creative applications of performance evaluation tools outside of those above and/or applications outside of those above are also welcome.A variety of types of submissions are possible, primarily original work, tutorials & surveys.Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center

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Sustainable Computing: Informatics and Systems

ISSN: 2210-5379
5 Year impact factor: 4.3
Impact factor: 3.8

Sustainable computing is a rapidly expanding research area spanning the fields of computer science and engineering, electrical engineering as well as other engineering disciplines. The aim of Sustainable Computing: Informatics and Systems (SUSCOM) is to publish the myriad research findings related to energy-aware and thermal-aware management of computing resource. Equally important is a spectrum of related research issues such as applications of computing that can have ecological and societal impacts. SUSCOM publishes original and timely research papers and survey articles in current areas of power, energy, temperature, and environment related research areas of current importance to readers. SUSCOM has an editorial board comprising prominent researchers from around the world and selects competitively evaluated peer-reviewed papers.Making computing sustainable - Software systems perspective: • Power-aware software • Code profiling and transformation for power management • Power-aware middleware • Multimedia systems • Scheduling and allocationComputing for sustainability - Use of computing to make the world a sustainable place: • Use of sensors for environmental monitoring • Smart control for eco-friendly buildings • Green Data Centers and Enterprise ComputingRe-inventing algorithms and applications for sustainability: • Theoretical aspect of energy, power, and temperature • Power-aware applications • Resource management to optimize performance and power • Power implications for portable and mobile computing • Algorithms for reduced power, energy and heat for high-performance computingModeling and evaluation of sustainable systems: • Reliability of Power-aware computers • Runtime systems that assist in power saving • Models for collective optimization of power and performance • Monitoring tools for power and performance of parallel and distributed systemsSustainable hardware platforms and devices - Hardware and architecture perspective: • Power aware networking • Real-time systems • Power-efficient architectures • Efficient circuit design for energy harvesting • Power management in memory, disk, storage and other peripheral devices • Configurable and renewable energy • Low power electronics • Embedded systems, ASICs and FPGSs • Power leakage and dissipationPlease submit your article via https://www.editorialmanager.com/suscom/default.aspx.

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Journals in Performance of systems

BenchCouncil Transactions on Benchmarks, Standards and Evaluations

Journal of Computational Science

Journal of Parallel and Distributed Computing

Parallel Computing

Performance Evaluation

Sustainable Computing: Informatics and Systems