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Constantin Pohl

dblp:201/6155 · DBLP profile ↗
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3ranked-venue papers
3as first author
0since 2021 · last 2020
0000-0002-5965-4047ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 3 · 3 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Query processing and optimization · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Memory systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Query processing and optimization › join processing › join algorithms
in-memory join		 0.412020
Joins on high-bandwidth memory: a new level in the memory hierarchy · VLDB J. 2020
Query processing and optimization
join processing		 0.412020
Joins on high-bandwidth memory: a new level in the memory hierarchy · VLDB J. 2020
Memory systems › DRAM › DRAM architecture
high bandwidth memory		 0.112020
Joins on high-bandwidth memory: a new level in the memory hierarchy · VLDB J. 2020
YearPublicationVenuePosition
2020 Joins on high-bandwidth memory: a new level in the memory hierarchy
Constantin Pohl, Kai-Uwe Sattler, Goetz Graefe
 VLDB J.1
2019 Adaptive Partitioning and Order-Preserved Merging of Data Streams
Constantin Pohl, Kai-Uwe Sattler
 ADBIS1
2018 Joins in a heterogeneous memory hierarchy: exploiting high-bandwidth memory
abstract
With High-Bandwidth Memory (HBM), an additional opportunity on hardware side for performance benefits is given. The large amount of available bandwidth compared to regular DRAM allows the execution of high numbers of threads in parallel masking penalties of concurrent memory accesses. This is especially interesting considering database join algorithms optimized for multicore CPUs, even more when running on a manycore processor like a Xeon Phi Knights Landing (KNL). The drawback of HBM, however, is its small size and given penalties in random memory access patterns.
Constantin Pohl, Kai-Uwe Sattler
 DaMoN1