D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 54 Citations 10,522 291 World Ranking 2348 National Ranking 1269

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Computer network
  • Programming language

His main research concerns Parallel computing, Computer network, Supercomputer, Distributed computing and Graphics processing unit. His research investigates the connection between Parallel computing and topics such as General-purpose computing on graphics processing units that intersect with problems in Symmetric multiprocessor system. His study in Supercomputer is interdisciplinary in nature, drawing from both Green computing, Embedded system and Mobile computing.

The study incorporates disciplines such as Scheduling, Reference data, Total cost of ownership and Computer maintenance in addition to Distributed computing. While the research belongs to areas of Graphics processing unit, he spends his time largely on the problem of Central processing unit, intersecting his research to questions surrounding Multi-core processor. His CUDA research includes elements of Programming paradigm and Graphics.

His most cited work include:

  • The design, implementation, and evaluation of mpiBLAST (365 citations)
  • A Power-Aware Run-Time System for High-Performance Computing (341 citations)
  • The Quadrics network: high-performance clustering technology (317 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Parallel computing, Distributed computing, Computer network, Supercomputer and CUDA. He has researched Parallel computing in several fields, including Scalability, Programming paradigm and General-purpose computing on graphics processing units. As part of one scientific family, Wu-chun Feng deals mainly with the area of Distributed computing, narrowing it down to issues related to the The Internet, and often Communications protocol.

The subject of his Supercomputer research is within the realm of Operating system. His CUDA study combines topics in areas such as Central processing unit, Kernel and Computational science. His Graphics processing unit research incorporates elements of Coprocessor, Massively parallel, Instruction set and Graphics.

He most often published in these fields:

  • Parallel computing (34.88%)
  • Distributed computing (26.16%)
  • Computer network (18.60%)

What were the highlights of his more recent work (between 2015-2021)?

  • Parallel computing (34.88%)
  • Speedup (11.34%)
  • Supercomputer (14.83%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Parallel computing, Speedup, Supercomputer, Field-programmable gate array and Scalability. His work carried out in the field of Parallel computing brings together such families of science as Scheduling, Data structure and Kernel. His Speedup study incorporates themes from Control reconfiguration, x86, Heuristic and Macro.

His work deals with themes such as Visualization, Programming paradigm and Unconventional computing, which intersect with Supercomputer. Wu-chun Feng has included themes like Computer architecture, Software portability and Compiler in his Field-programmable gate array study. His research integrates issues of Distributed computing, Deep learning, Artificial intelligence, Bottleneck and Implementation in his study of Scalability.

Between 2015 and 2021, his most popular works were:

  • Fast Detection of Transformed Data Leaks (42 citations)
  • Fast segmented sort on GPUs (40 citations)
  • Parallel Transposition of Sparse Data Structures (33 citations)

In his most recent research, the most cited papers focused on:

  • Operating system
  • Computer network
  • Programming language

Parallel computing, Scalability, Speedup, Programming paradigm and Supercomputer are his primary areas of study. His study of CUDA is a part of Parallel computing. His study focuses on the intersection of Scalability and fields such as Bottleneck with connections in the field of Deep learning and Data access.

Wu-chun Feng works mostly in the field of Speedup, limiting it down to topics relating to x86 and, in certain cases, Code, Vectorization, Multi-core processor and SIMD. In his study, which falls under the umbrella issue of Programming paradigm, Software portability, Symmetric multiprocessor system, Profiling and Hardware architecture is strongly linked to Field-programmable gate array. His Supercomputer research is multidisciplinary, incorporating elements of Ensemble learning, Frequency scaling and Decision tree.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

The Quadrics network: high-performance clustering technology

F. Petrini;Wu-chun Feng;A. Hoisie;S. Coll.
IEEE Micro (2002)

606 Citations

A Power-Aware Run-Time System for High-Performance Computing

Chung-hsing Hsu;Wu-chun Feng.
conference on high performance computing (supercomputing) (2005)

592 Citations

The design, implementation, and evaluation of mpiBLAST

A. E. Darling;L. Carey;W. C. Feng.
"Submitted to: ClusterWorld Conference&Expo 2003" (2003)

566 Citations

Inter-block GPU communication via fast barrier synchronization

Shucai Xiao;Wu-chun Feng.
international parallel and distributed processing symposium (2010)

339 Citations

FAST TCP: from theory to experiments

Cheng Jin;D. Wei;S.H. Low;J. Bunn.
IEEE Network (2005)

302 Citations

CPU MISER: A Performance-Directed, Run-Time System for Power-Aware Clusters

Rong Ge;Xizhou Feng;Wu-chun Feng;K.W. Cameron.
international conference on parallel processing (2007)

294 Citations

The Green500 List: Encouraging Sustainable Supercomputing

Wu-chun Feng;K.W. Cameron.
IEEE Computer (2007)

277 Citations

On the energy efficiency of graphics processing units for scientific computing

S. Huang;S. Xiao;W. Feng.
international parallel and distributed processing symposium (2009)

250 Citations

MOON: MapReduce On Opportunistic eNvironments

Heshan Lin;Xiaosong Ma;Jeremy Archuleta;Wu-chun Feng.
high performance distributed computing (2010)

222 Citations

The Failure of TCP in High-Performance Computational Grids

W. Feng;P. Tinnakornsrisuphap.
conference on high performance computing (supercomputing) (2000)

215 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Wu-chun Feng

Dhabaleswar K. Panda

Dhabaleswar K. Panda

The Ohio State University

Publications: 61

Enrique S. Quintana-Ortí

Enrique S. Quintana-Ortí

Universitat Politècnica de València

Publications: 35

Fabrizio Petrini

Fabrizio Petrini

Intel (United States)

Publications: 34

Luca Benini

Luca Benini

University of Bologna

Publications: 32

Pavan Balaji

Pavan Balaji

Argonne National Laboratory

Publications: 30

Karsten Schwan

Karsten Schwan

Georgia Institute of Technology

Publications: 25

José Duato

José Duato

Universitat Politècnica de València

Publications: 25

Ron Brightwell

Ron Brightwell

Sandia National Laboratories

Publications: 25

Satoshi Matsuoka

Satoshi Matsuoka

University of Tokyo

Publications: 23

Jun Wang

Jun Wang

University of Central Florida

Publications: 20

Torsten Hoefler

Torsten Hoefler

ETH Zurich

Publications: 20

Laxmikant V. Kale

Laxmikant V. Kale

University of Illinois at Urbana-Champaign

Publications: 19

Frank Mueller

Frank Mueller

North Carolina State University

Publications: 16

Bronis R. de Supinski

Bronis R. de Supinski

Lawrence Livermore National Laboratory

Publications: 16

Mateo Valero

Mateo Valero

Barcelona Supercomputing Center

Publications: 16

Lizhe Wang

Lizhe Wang

China University of Geosciences

Publications: 16

Trending Scientists

Rainer Leupers

Rainer Leupers

RWTH Aachen University

Klaus M. Schmidt

Klaus M. Schmidt

Ludwig-Maximilians-Universität München

Daniel O. Cajueiro

Daniel O. Cajueiro

University of Brasília

Christof Schulz

Christof Schulz

University of Duisburg-Essen

Michael R. Buchmeiser

Michael R. Buchmeiser

University of Stuttgart

Garland R. Marshall

Garland R. Marshall

Washington University in St. Louis

Xue‐Yuan Liu

Xue‐Yuan Liu

Lanzhou University

Miao Zhang

Miao Zhang

Beijing Jiaotong University

Patrice Codogno

Patrice Codogno

Université Paris Cité

Miguel G. Guerrero

Miguel G. Guerrero

Spanish National Research Council

Edward R. B. Moore

Edward R. B. Moore

University of Gothenburg

Hugh Montgomery

Hugh Montgomery

University College London

Nick Freemantle

Nick Freemantle

University College London

George C. Patton

George C. Patton

Murdoch Children's Research Institute

Gustavo Yepes

Gustavo Yepes

Autonomous University of Madrid

Andrew J. Benson

Andrew J. Benson

Carnegie Learning

Something went wrong. Please try again later.