Demo Data from EDBT 2026 / reviewers in the wild / expert
Victor Demjanenko
dblp:00/2768
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval
search engines |
0.0 | 1 | 1996 | 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 |
0.0 | 1 | 1996 | Parallel Intersecting Compressed Bit Vectors in a High Speed Query Server for Processing Postal Addresses · HPCA 1996 |
Parallel and multicore computing
parallel computing |
0.0 | 1 | 1996 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1996 | Parallel Intersecting Compressed Bit Vectors in a High Speed Query Server for Processing Postal AddressesabstractA 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 |
HPCA | 3 |
| 1990 | Adjacency algorithms for linear octree nodes
Djaffer Ibaroudene, Victor Demjanenko, Raj Acharya |
Image Vis. Comput. | 2 |