Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- Acknowledgements
- 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
- References
- Index
8 - GPU for Spatial Data: A Case Study in Pathology Imaging Applications
Published online by Cambridge University Press: 21 November 2024
Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- Acknowledgements
- 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
- References
- Index
Summary
Focusing on the intricate world of spatial data management, this chapter offers an in-depth analysis of how spatial data management tasks, specifically in the context of pathology imaging applications, are approached and optimized on traditional CPU-based computing platforms versus GPU-accelerated platforms. Employing a case-study methodology, the chapter not only delves into the specifics of these applications but also extrapolates broader methodologies and strategies for leveraging advanced hardware to enhance application performance.
- Type
- Chapter
- Information
- Data ManagementInteractions with Computer Architecture and Systems, pp. 203 - 236Publisher: Cambridge University PressPrint publication year: 2024