Exascale computing and big data

Author:

Reed Daniel A.1,Dongarra Jack2

Affiliation:

1. University of Iowa

2. University of Manchester

Abstract

Scientific discovery and engineering innovation requires unifying traditionally separated high-performance computing and big data analytics.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Cited by 293 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Spatial/Temporal Locality-based Load-sharing in Speculative Discrete Event Simulation on Multi-core Machines;ACM Transactions on Modeling and Computer Simulation;2024-01-08

2. Computational Storage for 3D NAND Flash Error Recovery Flow Prediction;Lecture Notes in Electrical Engineering;2023-11-29

3. A Systematic Mapping Study of Italian Research on Workflows;Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis;2023-11-12

4. End-to-End Workflows for Climate Science: Integrating HPC Simulations, Big Data Processing, and Machine Learning;Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis;2023-11-12

5. Forecasting File Lifecycles for Intelligent Data Placement in Hierarchical Storage;2023 IEEE 35th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD);2023-10-17

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