Dennis Heinrich

Orcid: 0000-0001-8674-8658

According to our database1, Dennis Heinrich authored at least 16 papers between 2014 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2020
Hardware-aided update acceleration in a hybrid Semantic Web database system.
J. Supercomput., 2020

2019
Parallel execution approaches on data and index structures in the context of semantic web database management systems.
PhD thesis, 2019

2018
Hardware-Accelerated Index Construction for Semantic Web.
Proceedings of the International Conference on Field-Programmable Technology, 2018

2017
Semi-static operator graphs for accelerated query execution on FPGAs.
Microprocess. Microsystems, 2017

Hardware-Accelerated Radix-Tree Based String Sorting for Big Data Applications.
Proceedings of the Architecture of Computing Systems - ARCS 2017, 2017

2016
Runtime Adaptive Hybrid Query Engine based on FPGAs.
Open J. Databases, 2016

Constructing Large-Scale Semantic Web Indices for the Six RDF Collation Orders.
Open J. Big Data, 2016

Accelerated join evaluation in Semantic Web databases by using FPGAs.
Concurr. Comput. Pract. Exp., 2016

2015
Distributed Join Approaches for W3C-Conform SPARQL Endpoints.
Open J. Semantic Web, 2015

PatTrieSort - External String Sorting based on Patricia Tries.
Open J. Databases, 2015

Automated composition and execution of hardware-accelerated operator graphs.
Proceedings of the 10th International Symposium on Reconfigurable Communication-centric Systems-on-Chip, 2015

Hybrid FPGA approach for a B<sup>+</sup> tree in a Semantic Web database system.
Proceedings of the 10th International Symposium on Reconfigurable Communication-centric Systems-on-Chip, 2015

An optimized radix-tree for hardware-accelerated dictionary generation for semantic web databases.
Proceedings of the International Conference on ReConFigurable Computing and FPGAs, 2015

2014
P-LUPOSDATE: Using Precomputed Bloom Filters to Speed Up SPARQL Processing in the Cloud.
Open J. Semantic Web, 2014

A Self-Optimizing Cloud Computing System for Distributed Storage and Processing of Semantic Web Data.
Open J. Cloud Comput., 2014

Parallel and Pipelined Filter Operator for Hardware-Accelerated Operator Graphs in Semantic Web Databases.
Proceedings of the 14th IEEE International Conference on Computer and Information Technology, 2014


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