H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 38 Citations 20,843 96 World Ranking 5006 National Ranking 2465

Research.com Recognitions

Awards & Achievements

2013 - SIAM Fellow For contributions to parallel computing and computational science.

2009 - ACM Gordon Bell Prize The Cat is Out of the Bag: Cortical Simulations with 109 Neurons, 1013 Synapses

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Algorithm
  • Statistics

His scientific interests lie mostly in Parallel computing, Algorithm, Combinatorics, Cluster analysis and Lanczos algorithm. His Parallel computing study integrates concerns from other disciplines, such as Kernel and Computational science. Horst D. Simon works mostly in the field of Algorithm, limiting it down to topics relating to Eigenvalues and eigenvectors and, in certain cases, Stability and Maxima and minima.

His Combinatorics research incorporates elements of Discrete mathematics, QR decomposition and Gramian matrix. The various areas that Horst D. Simon examines in his Cluster analysis study include Adjacency matrix, Matrix and Graph partition. His Supercomputer research is multidisciplinary, incorporating elements of Unified Parallel C and Massively parallel.

His most cited work include:

  • The Nas Parallel Benchmarks (2023 citations)
  • Partitioning sparse matrices with eigenvectors of graphs (1448 citations)
  • A min-max cut algorithm for graph partitioning and data clustering (733 citations)

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

Horst D. Simon spends much of his time researching Supercomputer, Parallel computing, Computational science, Algorithm and Eigenvalues and eigenvectors. His TOP500 study in the realm of Supercomputer interacts with subjects such as National laboratory. Horst D. Simon specializes in Parallel computing, namely Massively parallel.

His Computational science research incorporates themes from Parallel algorithm, Parallel processing, Visualization, Software and MIMD. Horst D. Simon interconnects Dimension, Sparse matrix, Laplacian matrix and Cluster analysis in the investigation of issues within Algorithm. As a part of the same scientific study, Horst D. Simon usually deals with the Eigenvalues and eigenvectors, concentrating on Applied mathematics and frequently concerns with Mathematical optimization.

He most often published in these fields:

  • Supercomputer (29.21%)
  • Parallel computing (25.84%)
  • Computational science (14.04%)

What were the highlights of his more recent work (between 2006-2020)?

  • Supercomputer (29.21%)
  • Parallel computing (25.84%)
  • Data science (7.30%)

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

His primary areas of investigation include Supercomputer, Parallel computing, Data science, Futures contract and Massively parallel. His Supercomputer study combines topics from a wide range of disciplines, such as Emerging technologies and Computer engineering. His work deals with themes such as Solver, Data structure and Fortran, which intersect with Parallel computing.

His Data science study combines topics in areas such as Field, Computing Methodologies and TOP500. His work carried out in the field of Massively parallel brings together such families of science as Load balancing, Theoretical computer science, Distributed memory and Partition. His research in Algorithm tackles topics such as Hermitian matrix which are related to areas like Mathematical optimization.

Between 2006 and 2020, his most popular works were:

  • The cat is out of the bag: cortical simulations with 109 neurons, 1013 synapses (230 citations)
  • Compass: a scalable simulator for an architecture for cognitive computing (103 citations)
  • A learning framework using Green's function and kernel regularization with application to recommender system (50 citations)

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

  • Operating system
  • Algorithm
  • Statistics

Horst D. Simon mostly deals with Supercomputer, Parallel computing, Mathematical optimization, Data science and Massively parallel. His research integrates issues of Computing Methodologies, Work in process and FLOPS in his study of Supercomputer. His study brings together the fields of Computation and Parallel computing.

His Mathematical optimization research focuses on subjects like Algorithm, which are linked to Hermitian matrix, Eigenvalues and eigenvectors, Lanczos resampling and Semi-supervised learning. He has researched Data science in several fields, including Data-driven, Computer architecture, TOP500 and Metric. His studies in Massively parallel integrate themes in fields like Scalability and Theoretical computer science.

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.

Top Publications

The NAS parallel benchmarks—summary and preliminary results

D. H. Bailey;E. Barszcz;J. T. Barton;D. S. Browning.
conference on high performance computing (supercomputing) (1991)

3605 Citations

The Nas Parallel Benchmarks

D.H. Bailey;E. Barszcz;J.T. Barton;D.S. Browning.
ieee international conference on high performance computing data and analytics (1991)

3342 Citations

Partitioning sparse matrices with eigenvectors of graphs

Alex Pothen;Horst D. Simon;Kan-Pu Liou.
SIAM Journal on Matrix Analysis and Applications (1990)

2346 Citations

Partitioning of unstructured problems for parallel processing

H.D. Simon.
Computing Systems in Engineering (1991)

1163 Citations

A min-max cut algorithm for graph partitioning and data clustering

C.H.Q. Ding;Xiaofeng He;Xiaofeng He;Hongyuan Zha;Ming Gu.
international conference on data mining (2001)

1085 Citations

Fast multilevel implementation of recursive spectral bisection for partitioning unstructured problems

Stephen T. Barnard;Horst D. Simon.
Concurrency and Computation: Practice and Experience (1994)

854 Citations

Spectral Relaxation for K-means Clustering

Hongyuan Zha;Xiaofeng He;Chris Ding;Ming Gu.
neural information processing systems (2001)

793 Citations

A Shifted Block Lanczos Algorithm for Solving Sparse Symmetric Generalized Eigenproblems

Roger G. Grimes;John G. Lewis;Horst D. Simon.
SIAM Journal on Matrix Analysis and Applications (1994)

583 Citations

Bipartite graph partitioning and data clustering

Hongyuan Zha;Xiaofeng He;Chris Ding;Horst Simon.
conference on information and knowledge management (2001)

462 Citations

The Lanczos algorithm with partial reorthogonalization

Horst D. Simon.
Mathematics of Computation (1984)

414 Citations

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

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