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Fengbin Qi

dblp:83/7449 · DBLP profile ↗
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4ranked-venue papers
1as first author
1since 2021 · last 2021
—ORCID · none

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

Databases, data management, data science and information retrieval · 2Systems, architecture and hardware · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

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
High-performance computing · 87% Processor architecture and microarchitecture · 13%

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

TopicWeightPapersLastEvidence papers
High-performance computing › supercomputing
exascale computing
0.512021
Sunway supercomputer architecture towards exascale computing: analysis and practice · Sci. China Inf. Sci. 2021
High-performance computing
supercomputer architecture
0.512021
Sunway supercomputer architecture towards exascale computing: analysis and practice · Sci. China Inf. Sci. 2021
Processor architecture and microarchitecture
many-core architecture
0.112021
Sunway supercomputer architecture towards exascale computing: analysis and practice · Sci. China Inf. Sci. 2021
YearPublicationVenuePosition
2021 Sunway supercomputer architecture towards exascale computing: analysis and practice
Jiangang Gao, Fang Zheng 0015, Fengbin Qi, Yajun Ding, Hongsheng Lu, Wangquan He, Hongmei Wei, Lifeng Jin, Daoyong Gong, Honghui Sun, Hongtao You
Sci. China Inf. Sci.3
2018 Modeling and Evaluating MID1 ICAL Pipeline on Spark
Zhongsheng Li, Wei Wang 0009, Fengbin Qi, Mingmin Chi
DASFAA (2)5
2018 HDUMP: A Data Recovery Tool for Hadoop
Zhongsheng Li, Wei Wang 0009, Qitong Wang 0003, Fengbin Qi, Peng Wang 0027
DASFAA (2)5
2009 RCC: A New Programming Language for Reconfigurable Computing
abstract
Reconfigurable computing is one of the most important developing directions of future high-performance computing, it combines the flexibility of general processors and the high efficiency of ASIC. Reconfigurable computing technology can make use of system resources sufficiently and exert the efficiency of the applications. Reconfigurable programming environment is the key to popularize reconfigurable computing technology. Software engineers can program FPGA by using reconfigurable programming language, and moreover, the reconfigurable compiler can provide an architecture-independent developing platform for high-level language programmers in order that they can use the reconfigurable computing system flexibly. Three typical reconfigurable computing systems are analyzed in this paper, including SGI RASC RC100, Cray XD1 and SRC-6E. Some typical reconfigurable programming environments are introduced, such as the Mitrion-C platform, the Impulse-C platform, etc. However, neither of them is convenient enough for software engineers to program FPGA. In this paper, a more useful reconfigurable programming language called RCC (Reconfigurable Computing C) is proposed. It is based on the subset of ANSI-C and extends some data types and functions. A RCC compiler is built to translate the RCC applications into VHDL description. Users can program FPGA easily by using the RCC language if they are familiar with ANSI-C. On FPGA simulator, we test 3 applications and get about 19X speedup. Furthermore, it is easier to use than some typical reconfigurable programming languages.
Fengbin Qi, Xianyi Zhang, Xingquan Mao
HPCC1