Data Management
Interactions with Computer Architecture and Systems

This guide explores the synergy of hardware, software, and data management in modern computing, blending techniques with practical insights.

Xiaodong Zhang (Author), Rubao Lee (Author)

9781009123310, Cambridge University Press

Hardback, published 28 November 2024

304 pages
24.9 x 17.7 x 2.3 cm, 0.71 kg

'The hardware platforms on which database systems are developed have changed drastically since the early days of databases. The last 2+ decades have seen the research and development community study the impact of these changes on the database system architecture and internals and significant developments have occurred. The relationship between database systems and operating systems have been a concern since at least 1880s. We have not had a coherent book that covers the complex interactions between database systems, operating systems and the underlying hardware platform. This book by Zhang and Lee provides an excellent coverage of this area. I enjoyed reading it and I expect it to be very useful in our teaching.' M. Tamer Özsu, University of Waterloo

This guide illuminates the intricate relationship between data management, computer architecture, and system software. It traces the evolution of computing to today's data-centric focus and underscores the importance of hardware-software co-design in achieving efficient data processing systems with high throughput and low latency. The thorough coverage includes topics such as logical data formats, memory architecture, GPU programming, and the innovative use of ray tracing in computational tasks. Special emphasis is placed on minimizing data movement within memory hierarchies and optimizing data storage and retrieval. Tailored for professionals and students in computer science, this book combines theoretical foundations with practical applications, making it an indispensable resource for anyone wanting to master the synergies between data management and computing infrastructure.

About the authors
Preface
1. Introduction
2. Data storage: physical allocation and logical format
3. Main memory: the physical space
4. Buffer replacement algorithms
5. In-memory data processing in large data centers
6. GPU computing: a new algorithm-to-architecture interaction
7. GPU for structured data
8. GPU for spatial data: a case study in pathology imaging applications
9. Ray tracing hardware in GPUs for accelerated computation
10. The future of computing – synergies in data management and system architecture
Bibliography
Index.

Subject Areas: Databases [UN]