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Taowei Luo

dblp:165/2093 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · none

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

Systems, architecture and hardware · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 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.

Software engineering, system software, and programming languages
1 paper
Operating systems · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%

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

TopicWeightPapersLastEvidence papers
Operating systems › resource management › memory management
huge pages
0.312017
Evaluating the impacts of hugepage on virtual machines · Sci. China Inf. Sci. 2017
Operating systems › resource management › memory management
virtual memory
0.312017
Evaluating the impacts of hugepage on virtual machines · Sci. China Inf. Sci. 2017
Cloud and datacenter computing › virtualization
virtual machine
0.112017
Evaluating the impacts of hugepage on virtual machines · Sci. China Inf. Sci. 2017

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

virtualization · 0.6huge pages · 0.6
YearPublicationVenuePosition
2017 Evaluating the impacts of hugepage on virtual machines
Xiaolin Wang 0001, Taowei Luo, Zhenlin Wang 0003, Yingwei Luo
Sci. China Inf. Sci.2
2015 Improving TLB Performance by Increasing Hugepage Ratio
abstract
Linux supports transparent huge page since 2.6.38. It can automatically map huge pages. But this implementation fails to adjust to page alignment in memory allocation and thus cannot use huge page in some situations. The design is not efficient. Our work aims to increase huge page allocation, so as to improve the utilization ratio of huge page and overall performance. The experimental results show that the optimization almost reaches the upper bound of huge page utilization. This software approach delivers a notable performance improvement for a few benchmarks with moderate overhead in physical memory consumption.
Taowei Luo, Xiaolin Wang 0001, Yingwei Luo, Zhenlin Wang 0003
CCGRID1