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Kyeongyeol Lim

dblp:139/2567 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

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

Systems, 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
Storage systems · 50% Processor architecture and microarchitecture · 50%

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

TopicWeightPapersLastEvidence papers
Storage systems › data reduction
data deduplication
0.212015
MUCH: Multithreaded Content-Based File Chunking · IEEE Trans. Computers 2015
Processor architecture and microarchitecture › multithreading
multithreaded execution
0.212015
MUCH: Multithreaded Content-Based File Chunking · IEEE Trans. Computers 2015

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

performance modeling · 0.2
YearPublicationVenuePosition
2015 MUCH: Multithreaded Content-Based File Chunking
abstract
In this work, we developed a novel multithreaded variable size chunking method, MUCH, which exploits the multicore architecture of the modern microprocessors. The legacy single threaded variable size chunking method leaves much to be desired in terms of effectively exploiting the bandwidth of the state of the art storage devices. MUCH guaranteeschunking invariability: The result of chunking does not change regardless of the degree of multithreading or the segment size. This is achieved by inter and intra-segment coalescing at the master thread and Dual Mode Chunking at the client thread. We developed an elaborate performance model to determine the optimal multithreading degree and the segment size. MUCH is implemented in the prototype deduplication system. By fully exploiting the available CPU cores (quad-core), we achieved up to$\times$4 increase in the chunking performance (MByte/sec). MUCH successfully addresses the performance issues of file chunking which is one of the performance bottlenecks in modern deduplication systems by parallelizing the file chunking operation while guaranteeing Chunking Invariability.
Youjip Won, Kyeongyeol Lim, Jaehong Min
IEEE Trans. Computers2