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 53 Citations 9,204 282 World Ranking 2512 National Ranking 67

Research.com Recognitions

Awards & Achievements

2020 - ACM Senior Member

2019 - ACM Gordon Bell Prize For A Data-Centric Approach to Extreme-Scale Ab initio Dissipative Quantum Transport Simulations

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Programming language
  • Computer network

His main research concerns Distributed computing, Parallel computing, Message Passing Interface, Scalability and Supercomputer. Torsten Hoefler studies Distributed computing, focusing on Message passing in particular. His Parallel computing research includes elements of Conjugate gradient solver, Computation, Stencil and Programming paradigm.

His study on Message Passing Interface also encompasses disciplines like

  • Semantics which connect with Remote memory access and Shared memory,
  • Interface that connect with fields like Memory footprint and SIMPLE. His Scalability research focuses on subjects like Fortran, which are linked to Programmer, Volume and Remote direct memory access. In his study, Memory bandwidth, Atmospheric model and Bottleneck is inextricably linked to Compiler, which falls within the broad field of Supercomputer.

His most cited work include:

  • Demystifying Parallel and Distributed Deep Learning: An In-depth Concurrency Analysis (229 citations)
  • The PERCS High-Performance Interconnect (173 citations)
  • Characterizing the Influence of System Noise on Large-Scale Applications by Simulation (166 citations)

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

His primary scientific interests are in Distributed computing, Parallel computing, Scalability, Computer network and Network topology. His Distributed computing research includes themes of Implementation, Computation and InfiniBand. As a part of the same scientific family, he mostly works in the field of Parallel computing, focusing on Programming paradigm and, on occasion, Theoretical computer science.

The Scalability study combines topics in areas such as Computer architecture and Supercomputer. His Network packet and Multipath routing study are his primary interests in Computer network. His Message Passing Interface study frequently draws connections to adjacent fields such as Interface.

He most often published in these fields:

  • Distributed computing (28.87%)
  • Parallel computing (22.94%)
  • Scalability (18.30%)

What were the highlights of his more recent work (between 2019-2021)?

  • Parallel computing (22.94%)
  • Artificial intelligence (6.70%)
  • Scalability (18.30%)

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

His primary areas of study are Parallel computing, Artificial intelligence, Scalability, Graph and Deep learning. As a part of the same scientific study, Torsten Hoefler usually deals with the Artificial intelligence, concentrating on Machine learning and frequently concerns with Set. His research in Scalability intersects with topics in Computer architecture, Compiler, Middleware, Distributed computing and Latency.

His Compiler study integrates concerns from other disciplines, such as Supercomputer and Solver. His study in Distributed computing is interdisciplinary in nature, drawing from both Interconnection, Ethernet protocol and Interoperability. Torsten Hoefler works mostly in the field of Graph, limiting it down to concerns involving Graph and, occasionally, Graph theory, Heuristics and Algorithm.

Between 2019 and 2021, his most popular works were:

  • Kilometer-scale climate models: Prospects and challenges (18 citations)
  • Augment Your Batch: Improving Generalization Through Instance Repetition (17 citations)
  • Taming unbalanced training workloads in deep learning with partial collective operations (14 citations)

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

  • Operating system
  • Programming language
  • Computer network

His primary areas of investigation include Artificial intelligence, Set, Deep learning, Artificial neural network and Compiler. As a member of one scientific family, he mostly works in the field of Artificial intelligence, focusing on Machine learning and, on occasion, Scalability and Forecast skill. His Set research is multidisciplinary, incorporating perspectives in Software, Reusability, Sparse matrix, Distributed algorithm and System on a chip.

His Deep learning study incorporates themes from Stochastic gradient descent, Convergence, Asynchronous communication, Training and Phrase. His work carried out in the field of Compiler brings together such families of science as Source lines of code and Code. His work on Parallel computing is being expanded to include thematically relevant topics such as Stencil.

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

Characterizing the Influence of System Noise on Large-Scale Applications by Simulation

Torsten Hoefler;Timo Schneider;Andrew Lumsdaine.
ieee international conference on high performance computing data and analytics (2010)

277 Citations

Generic topology mapping strategies for large-scale parallel architectures

Torsten Hoefler;Marc Snir.
international conference on supercomputing (2011)

272 Citations

The PERCS High-Performance Interconnect

Baba Arimilli;Ravi Arimilli;Vicente Chung;Scott Clark.
high performance interconnects (2010)

263 Citations

Demystifying Parallel and Distributed Deep Learning: An In-depth Concurrency Analysis

Tal Ben-Nun;Torsten Hoefler.
ACM Computing Surveys (2019)

257 Citations

Implementation and performance analysis of non-blocking collective operations for MPI

Torsten Hoefler;Andrew Lumsdaine;Wolfgang Rehm.
conference on high performance computing (supercomputing) (2007)

247 Citations

Slim fly: a cost effective low-diameter network topology

Maciej Besta;Torsten Hoefler.
ieee international conference on high performance computing data and analytics (2014)

242 Citations

LogGOPSim: simulating large-scale applications in the LogGOPS model

Torsten Hoefler;Timo Schneider;Andrew Lumsdaine.
high performance distributed computing (2010)

202 Citations

The Convergence of Sparsified Gradient Methods

Dan Alistarh;Torsten Hoefler;Mikael Johansson;Nikola Konstantinov.
neural information processing systems (2018)

176 Citations

Scientific benchmarking of parallel computing systems: twelve ways to tell the masses when reporting performance results

Torsten Hoefler;Roberto Belli.
ieee international conference on high performance computing data and analytics (2015)

173 Citations

Multistage switches are not crossbars: Effects of static routing in high-performance networks

T. Hoefler;T. Schneider;A. Lumsdaine.
international conference on cluster computing (2008)

153 Citations

Best Scientists Citing Torsten Hoefler

Dhabaleswar K. Panda

Dhabaleswar K. Panda

The Ohio State University

Publications: 65

William Gropp

William Gropp

University of Illinois at Urbana-Champaign

Publications: 38

Pavan Balaji

Pavan Balaji

Argonne National Laboratory

Publications: 38

Andrew Lumsdaine

Andrew Lumsdaine

Pacific Northwest National Laboratory

Publications: 35

Laxmikant V. Kale

Laxmikant V. Kale

University of Illinois at Urbana-Champaign

Publications: 28

Robert Ross

Robert Ross

Argonne National Laboratory

Publications: 23

Jack Dongarra

Jack Dongarra

University of Tennessee at Knoxville

Publications: 20

Mateo Valero

Mateo Valero

Barcelona Supercomputing Center

Publications: 20

Satoshi Matsuoka

Satoshi Matsuoka

University of Tokyo

Publications: 18

Aydin Buluc

Aydin Buluc

Lawrence Berkeley National Laboratory

Publications: 18

Christopher D. Carothers

Christopher D. Carothers

Rensselaer Polytechnic Institute

Publications: 18

Katherine Yelick

Katherine Yelick

Lawrence Berkeley National Laboratory

Publications: 16

Hideharu Amano

Hideharu Amano

Keio University

Publications: 16

George Bosilca

George Bosilca

University of Tennessee at Knoxville

Publications: 16

Yutaka Ishikawa

Yutaka Ishikawa

University of Tokyo

Publications: 15

David E. Keyes

David E. Keyes

King Abdullah University of Science and Technology

Publications: 15

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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