Benchmarking, Measuring, and Optimizing
15th BenchCouncil International Symposium, Bench 2023, Sanya, China, December 3-5, 2023, Revised Selected Papers
(Sprache: Englisch)
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...
The 11 full papers included in this book...
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Produktinformationen zu „Benchmarking, Measuring, and Optimizing “
Klappentext zu „Benchmarking, Measuring, and Optimizing “
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.
Inhaltsverzeichnis zu „Benchmarking, Measuring, and Optimizing “
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 forMolecular 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 GenerationCombining Statistical Modeling and Autoregressive Analysis.- Automated HPC Workload Generation Combining Statistical Modeling and Autoregressive Analysis.
Bibliographische Angaben
- 2024, 1st ed. 2024, XVI, 189 Seiten, 70 farbige Abbildungen, Masse: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: Sascha Hunold, Biwei Xie, Kai Shu
- Verlag: Springer, Berlin
- ISBN-10: 9819703158
- ISBN-13: 9789819703159
Sprache:
Englisch
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