15th BenchCouncil International Symposium, Bench 2023, Sanya, China, December 3–5, 2023, Revised Selected Papers Hunold, Sascha. editor. edt http://id.loc.gov/vocabulary/relators/edt Xie, Biwei. editor. edt http://id.loc.gov/vocabulary/relators/edt Shu, Kai. editor. edt http://id.loc.gov/vocabulary/relators/edt SpringerLink (Online service) text si 2024 1st ed. 2024. monographic eng

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access XVI, 189 p. 78 illus., 70 illus. in color. online resource. This book constitutes the refereed proceedings of the 14th BenchCouncil International Symposium on Benchmarking, Measuring, and Optimizing, Bench 2023, held in Sanya, China, during December 3–5, 2023. The 11 full papers included in this book were carefully reviewed and selected from 20 submissions. The Bench symposium invites papers that exhibit three defining characteristics: (1) It provides a high-quality, single-track forum for presenting results and discussing ideas that further the knowledge and understanding of the benchmark community; (2) It is a multi-disciplinary conference, attracting researchers and practitioners from different communities, including architecture, systems, algorithms, and applications; (3) The program features both invited and contributed talks. ICBench: Benchmarking Knowledge Mastery in Introductory Computer Science Education -- Generating High Dimensional Test Data for Topological Data Analysis -- Does AI for Science Need Another ImageNet or Totally Different Benchmarks? A Case Study of Machine Learning Force Fields -- MolBench: A Benchmark of AI Models for Molecular Property Prediction -- Cross-Layer Profiling of IoTBench -- MMDBench: A Benchmark for Hybrid Query in Multimodal Database -- Benchmarking Modern Databases for Storing and Profiling Very Large Scale HPC Communication Data -- A Linear Combination-based Method to Construct Proxy Benchmarks for Big Data Workloads -- AGIBench: A Multi-granularity, Multimodal, Human-referenced, Auto-scoring Benchmark for Large Language Models -- Automated HPC Workload Generation Combining Statistical Modeling and Autoregressive Analysis -- Automated HPC Workload Generation Combining Statistical Modeling and Autoregressive Analysis. edited by Sascha Hunold, Biwei Xie, Kai Shu. Application software Computer and Information Systems Applications QA76.76.A65 9789819703166 https://doi.org/10.1007/978-981-97-0316-6 https://doi.org/10.1007/978-981-97-0316-6 240213 20251030111810.0 978-981-97-0316-6