Scalable Data Management for Future Hardware
This open access book presents the results of the DFG priority program on Scalable Data Management for Future Hardware. It details requirements and solutions of how modern and future hardware architectures can be leveraged to address the challenges in modern data management. The nine chapters of the...
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| Hlavní autori: | , , , |
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| Médium: | E-kniha |
| Jazyk: | English |
| Vydavateľské údaje: |
Cham
Springer Nature
2025
Springer |
| Vydanie: | 1 |
| Predmet: | |
| ISBN: | 9783031740961, 3031740971, 9783031740978, 3031740963 |
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| Abstract | This open access book presents the results of the DFG priority program on Scalable Data Management for Future Hardware. It details requirements and solutions of how modern and future hardware architectures can be leveraged to address the challenges in modern data management. The nine chapters of the book present a wide range of data management architectures in conjunction with current hardware developments, often related to applications in data analytics or machine learning. They cover topics such as hardware-accelerated query or event processing on FPGA, GPU, and multicore CPUs, scalable data management in data center networks or on modern memory and storage technologies, and operating system support. This book provides researchers in academia and industry with a comprehensive combination of data management, operating systems, distributed systems and computer architecture issues necessary to address the requirements from practice as well as to propel innovative ideas and challenging research questions. |
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| AbstractList | This open access book presents the results of the DFG priority program on Scalable Data Management for Future Hardware. It details requirements and solutions of how modern and future hardware architectures can be leveraged to address the challenges in modern data management. The nine chapters of the book present a wide range of data management architectures in conjunction with current hardware developments, often related to applications in data analytics or machine learning. They cover topics such as hardware-accelerated query or event processing on FPGA, GPU, and multicore CPUs, scalable data management in data center networks or on modern memory and storage technologies, and operating system support. This book provides researchers in academia and industry with a comprehensive combination of data management, operating systems, distributed systems and computer architecture issues necessary to address the requirements from practice as well as to propel innovative ideas and challenging research questions. |
| Author | Neumann, Thomas Sattler, Kai-Uwe Teubner, Jens Kemper, Alfons |
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| Editor | Neumann, Thomas Sattler, Kai-Uwe Teubner, Jens Kemper, Alfons |
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| Title | Scalable Data Management for Future Hardware |
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