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Databases on modern hardware : how to stop underutilization and love multicores

Author: Anastassia Ailamaki; Erietta Liarou; Pinar Tözün; Danica Porobic; Iraklis Psaroudakis
Publisher: [San Rafael, California] : Morgan & Claypool Publishers, [2017] ©2017
Series: Synthesis lectures on data management, #45.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Data management systems enable various influential applications from high-performance online services (e.g., social networks like Twitter and Facebook or financial markets) to big data analytics (e.g., scientific exploration, sensor networks, business intelligence). As a result, data management systems have been one of the main drivers for innovations in the database and computer architecture communities for several  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
DATABASES ON MODERN HARDWARE.
[S.l.] : MORGAN & CLAYPOOL, 2017
(OCoLC)1006793629
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Anastassia Ailamaki; Erietta Liarou; Pinar Tözün; Danica Porobic; Iraklis Psaroudakis
ISBN: 9781681731544 1681731541
OCLC Number: 1001571974
Description: 1 online resource (xii, 101 pages) : illustrations.
Contents: 1. Introduction --
1.1 Implicit/vertical dimension --
1.2 Explicit/horizontal dimension --
1.3 Structure of the book. Part I. Implicit/vertical scalability. 2. Exploiting resources of a processor core --
2.1 Instruction and data parallelism --
2.2 Multithreading --
2.3 Horizontal parallelism --
2.3.1 Horizontal parallelism in advanced database scenarios --
2.3.2 Conclusions. 3. Minimizing memory stalls --
3.1 Workload characterization for typical data management workloads --
3.2 Roadmap for this chapter --
3.3 Prefetching --
3.3.1 Techniques that are common in modern hardware --
3.3.2 Temporal streaming --
3.3.3 Software-guided prefetching --
3.4 Being cache-conscious while writing software --
3.4.1 Code optimizations --
3.4.2 Data layouts --
3.4.3 Changing execution models --
3.5 Exploiting common instructions --
3.6 Conclusions. Part II. Explicit/horizontal scalability. 4. Scaling-up OLTP --
4.1 Focus on unscalable components --
4.1.1 Locking --
4.1.2 Latching --
4.1.3 Logging --
4.1.4 Synchronization --
4.2 Non-uniform communication --
4.3 Conclusions. 5. Scaling-up OLAP workloads --
5.1 Sharing across concurrent queries --
5.1.1 Reactive sharing --
5.1.2 Proactive sharing --
5.1.3 Systems with sharing techniques --
5.2 NUMA-awareness --
5.2.1 Analytical operators --
5.2.2 Task scheduling --
5.2.3 Coordinated data placement and task scheduling --
5.3 Conclusions. Part III. Conclusions. 6. Outlook --
6.1 Dark silicon and hardware specialization --
6.2 Non-volatile RAM and durability --
6.3 Hardware transactional memory --
6.4 Task scheduling for mixed workloads and energy efficiency. 7. Summary --
Bibliography --
Authors' biographies.
Series Title: Synthesis lectures on data management, #45.
Responsibility: Anastasia Ailamaki, Erietta Liarou, Pinar Tözün, Danica Porobic, Iraklis Psaroudakis.
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Abstract:

Data management systems have been one of the main drivers for innovations in the database and computer architecture communities for several decades. This book sheds light on the challenges present  Read more...

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