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Victor Demjanenko

dblp:00/2768 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1996
—ORCID · none

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 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.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Hardware accelerators and domain-specific architectures · 77% Parallel and multicore computing · 23%
Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%

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

TopicWeightPapersLastEvidence papers
Information retrieval
search engines
0.011996
Parallel Intersecting Compressed Bit Vectors in a High Speed Query Server for Processing Postal Addresses · HPCA 1996
Hardware accelerators and domain-specific architectures › database accelerator
query accelerator
0.011996
Parallel Intersecting Compressed Bit Vectors in a High Speed Query Server for Processing Postal Addresses · HPCA 1996
Parallel and multicore computing
parallel computing
0.011996
Parallel Intersecting Compressed Bit Vectors in a High Speed Query Server for Processing Postal Addresses · HPCA 1996

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

parallel intersection · 0.0hardware embedding · 0.0compressed bit vector · 0.0
YearPublicationVenuePosition
1996 Parallel Intersecting Compressed Bit Vectors in a High Speed Query Server for Processing Postal Addresses
abstract
A parallel architecture is proposed for a high speed query server to process postal addresses with several fields. For a given component in a field, the offset addresses of records which contain the component in a postal address database are coded into a Compressed Bit Vector (CBV). Finding the appropriate CBVs and performing intersections to get matching offset addresses are key bottleneck for the performance in the query server. They are accomplished by a specialized hardware embedded in a general purpose computer for a cost effective solution. This hardware directly operates on the CBVs using parallel schemes. The architecture and algorithms for expanding a CBV, for synchronizing the parallel processing of the processing units, and for balancing the load in the pipelined stages are presented with simulation results.
Wen-jann Yang, Ramalingam Sridhar, Victor Demjanenko
HPCA3
1990 Adjacency algorithms for linear octree nodes
Djaffer Ibaroudene, Victor Demjanenko, Raj Acharya
Image Vis. Comput.2