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Allan Bricker

dblp:04/6754 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 1991
—ORCID · none

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

Computer networks · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 1

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
Database system architecture and tuning · 50% Query processing and optimization · 25% Data stream processing · 25%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Database system architecture and tuning
database machine
0.011990
The Gamma Database Machine Project · IEEE Trans. Knowl. Data Eng. 1990
Data stream processing
dataflow scheduling
0.011990
The Gamma Database Machine Project · IEEE Trans. Knowl. Data Eng. 1990
Database system architecture and tuning
parallel database system
0.011990
The Gamma Database Machine Project · IEEE Trans. Knowl. Data Eng. 1990
Query processing and optimization
parallel query processing
0.011990
The Gamma Database Machine Project · IEEE Trans. Knowl. Data Eng. 1990
Parallel and multicore computing
dataflow computing
0.011990
The Gamma Database Machine Project · IEEE Trans. Knowl. Data Eng. 1990
Parallel and multicore computing
parallel programming models
0.011990
The Gamma Database Machine Project · IEEE Trans. Knowl. Data Eng. 1990

Methods — techniques the papers use, named apart from their topics

horizontal partitioning · 0.0hashing · 0.0
YearPublicationVenuePosition
1991 Architectural issues in microkernel-based operating systems: the CHORUS experience
Allan Bricker, Michel Gien, Marc Guillemont, Jim Lipkis, Doug Orr, Marc Rozier
Comput. Commun.1
1990 The Gamma Database Machine Project
abstract
The design of the Gamma database machine and the techniques employed in its implementation are described. Gamma is a relational database machine currently operating on an Intel iPSC/2 hypercube with 32 processors and 32 disk drives. Gamma employs three key technical ideas which enable the architecture to be scaled to hundreds of processors. First, all relations are horizontally partitioned across multiple disk drives, enabling relations to be scanned in parallel. Second, parallel algorithms based on hashing are used to implement the complex relational operators, such as join and aggregate functions. Third, dataflow scheduling techniques are used to coordinate multioperator queries. By using these techniques, it is possible to control the execution of very complex queries with minimal coordination. The design of the Gamma software is described and a thorough performance evaluation of the iPSC/s hypercube version of Gamma is presented.>
David J. DeWitt, Shahram Ghandeharizadeh, Donovan A. Schneider, Allan Bricker, Hui-I Hsiao, Rick Rasmussen
IEEE Trans. Knowl. Data Eng.4