Small Refinements to the DAM Can Have Big Consequences for Data-Structure Design-Reference-Cited by-同舟云学术

Small Refinements to the DAM Can Have Big Consequences for Data-Structure Design

Published:2019-06-17 Issue: Volume: Page:
ISSN:
Container-title:The 31st ACM Symposium on Parallelism in Algorithms and Architectures
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Author:

Bender Michael A.¹,Conway Alex²,Farach-Colton Martín³,Jannen William⁴,Jiao Yizheng⁵,Johnson Rob⁶,Knorr Eric³,McAllister Sara⁷,Mukherjee Nirjhar⁵,Pandey Prashant⁸,Porter Donald E.⁵,Yuan Jun⁹,Zhan Yang⁵

Affiliation:

1. Stony Brook University, Stony Brook, NY, USA

2. Rutgers University & VMware Research, New Brunswick, NJ, USA

3. Rutgers University, New Brunswick, NJ, USA

4. Williams College, Williamstown, MA, USA

5. The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

6. VMware Research, Palo Alto, CA, USA

7. Harvey Mudd College, Claremont, CA, USA

8. Carnegie Mellon University, Pittsburgh, PA, USA

9. Pace University, New York, NY, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3323165.3323210

Reference68 articles.

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3. Lars Arge. 2002. External Memory Geometric Data Structures. Lecture notes of EEF Summer School on Massive Data Sets Aarhus (2002). Lars Arge. 2002. External Memory Geometric Data Structures. Lecture notes of EEF Summer School on Massive Data Sets Aarhus (2002).

4. Microsoft Azure. 2016. How to use batching to improve SQL Database application performance. https://docs.microsoft.com/en-us/azure/sql-database/sql-database-use-batching-to-improve-performance . Microsoft Azure. 2016. How to use batching to improve SQL Database application performance. https://docs.microsoft.com/en-us/azure/sql-database/sql-database-use-batching-to-improve-performance .

5. Organization and maintenance of large ordered indexes

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