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Zhongwen Ying

dblp:145/7898 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2014
—ORCID · none

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

Systems, architecture and hardware · 1 · 1 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.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 44% Interconnection networks and networks-on-chip · 44% Performance modeling and evaluation · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interconnection networks and networks-on-chip
network topology
0.212014
Signature Searching in a Networked Collection of Files · IEEE Trans. Parallel Distributed Syst. 2014
Parallel and multicore computing › parallel algorithms
parallel search
0.212014
Signature Searching in a Networked Collection of Files · IEEE Trans. Parallel Distributed Syst. 2014

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

simulation · 0.2analytical modeling · 0.2
YearPublicationVenuePosition
2014 Signature Searching in a Networked Collection of Files
abstract
A signature is a data pattern of interest in a large data file or set of large data files. Such signatures that need to be found arise in applications such as DNA sequence analysis, network intrusion detection, biometrics, large scientific experiments, speech recognition and sensor networks. Related to this is string matching. More specifically we envision a problem where long linear data files (i.e., flat files) contain multiple signatures that are to be found using a multiplicity of processors (parallel processor). This paper evaluates the performance of finding signatures in files residing in the nodes of parallel processors configured as trees, two dimensional meshes and hypercubes. We assume various combinations of sequential and parallel searching. A unique feature of this work is that it is assumed that data is pre-loaded onto processors, as may occur in practice, thus load distribution time need not be accounted for. Elegant expressions are found for average signature searching time and speedup, and graphical results are provided.
Zhongwen Ying, Thomas G. Robertazzi
IEEE Trans. Parallel Distributed Syst.1