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 33 Citations 5,597 282 World Ranking 6657 National Ranking 89

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Programming language
  • Parallel computing

The scientist’s investigation covers issues in Parallel computing, Linear algebra, Algorithm, CUDA and Multi-core processor. His Parallel computing research is multidisciplinary, incorporating perspectives in Scheduling, Dynamic priority scheduling, Computation and Graphics. Enrique S. Quintana-Ortí interconnects Programming language, Numerical linear algebra and LU decomposition in the investigation of issues within Linear algebra.

His Algorithm study integrates concerns from other disciplines, such as Truncation, Matrix and Implementation. His CUDA research incorporates elements of Virtualization and Coprocessor. His Multi-core processor research is multidisciplinary, incorporating elements of Software portability, Xeon and Programming paradigm.

His most cited work include:

  • rCUDA: Reducing the number of GPU-based accelerators in high performance clusters (197 citations)
  • An Extension of the StarSs Programming Model for Platforms with Multiple GPUs (135 citations)
  • iMODS: internal coordinates normal mode analysis server (133 citations)

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

His scientific interests lie mostly in Parallel computing, Multi-core processor, Linear system, Linear algebra and Matrix. Enrique S. Quintana-Ortí mostly deals with Supercomputer in his studies of Parallel computing. His biological study deals with issues like CUDA, which deal with fields such as Coprocessor.

His Multi-core processor research includes themes of Scalability, Task parallelism, Energy consumption, Scheduling and Efficient energy use. His research in Linear algebra intersects with topics in Sparse matrix, Cholesky decomposition and Implementation. His study looks at the intersection of Matrix and topics like Algorithm with Factorization.

He most often published in these fields:

  • Parallel computing (54.50%)
  • Multi-core processor (25.75%)
  • Linear system (22.00%)

What were the highlights of his more recent work (between 2016-2021)?

  • Parallel computing (54.50%)
  • Multi-core processor (25.75%)
  • Linear system (22.00%)

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

Enrique S. Quintana-Ortí mostly deals with Parallel computing, Multi-core processor, Linear system, Matrix and Linear algebra. His research integrates issues of Factorization, Sparse matrix, LU decomposition, Graphics and Solver in his study of Parallel computing. His work deals with themes such as Multithreading, Leverage, Scheduling, Efficient energy use and Kernel, which intersect with Multi-core processor.

Enrique S. Quintana-Ortí has included themes like Iterative method, Scaling and Conjugate gradient method in his Linear system study. The concepts of his Matrix study are interwoven with issues in Algorithm, Reduction and Graphics processing unit. His work carried out in the field of Linear algebra brings together such families of science as Artificial neural network, Voltage frequency scaling, Supercomputer and Xeon.

Between 2016 and 2021, his most popular works were:

  • Adaptive Precision in Block-Jacobi Preconditioning for Iterative Sparse Linear System Solvers (27 citations)
  • Batched Gauss-Jordan Elimination for Block-Jacobi Preconditioner Generation on GPUs (13 citations)
  • A Case for Malleable Thread-Level Linear Algebra Libraries: The LU Factorization With Partial Pivoting (8 citations)

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

  • Operating system
  • Parallel computing
  • Programming language

His primary areas of investigation include Parallel computing, Linear system, Linear algebra, LU decomposition and Matrix. A large part of his Parallel computing studies is devoted to Multi-core processor. His Linear system study combines topics in areas such as Positive-definite matrix and Floating point.

The study incorporates disciplines such as Factorization, Supercomputer and Significand in addition to Linear algebra. His LU decomposition study incorporates themes from Iterative method, Algorithm, Pivot element and Theoretical computer science. His study in the field of Matrix decomposition also crosses realms of Focus.

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

rCUDA: Reducing the number of GPU-based accelerators in high performance clusters

Jose Duato;Antonio J. Pena;Federico Silla;Rafael Mayo.
international conference on high performance computing and simulation (2010)

325 Citations

An Extension of the StarSs Programming Model for Platforms with Multiple GPUs

Eduard Ayguadé;Rosa M. Badia;Francisco D. Igual;Jesús Labarta.
european conference on parallel processing (2009)

218 Citations

The science of deriving dense linear algebra algorithms

Paolo Bientinesi;John A. Gunnels;Margaret E. Myers;Enrique S. Quintana-Ortí.
ACM Transactions on Mathematical Software (2005)

212 Citations

Solving stable generalized Lyapunov equations with the matrix sign function

Peter Benner;Peter Benner;Enrique S. Quintana-Ortí.
Numerical Algorithms (1999)

202 Citations

Supermatrix out-of-order scheduling of matrix operations for SMP and multi-core architectures

Ernie Chan;Enrique S. Quintana-Orti;Gregorio Quintana-Orti;Robert van de Geijn.
acm symposium on parallel algorithms and architectures (2007)

180 Citations

Programming matrix algorithms-by-blocks for thread-level parallelism

Gregorio Quintana-Ortí;Enrique S. Quintana-Ortí;Robert A. Van De Geijn;Field G. Van Zee.
ACM Transactions on Mathematical Software (2009)

175 Citations

Solving dense linear systems on platforms with multiple hardware accelerators

Gregorio Quintana-Ortí;Francisco D. Igual;Enrique S. Quintana-Ortí;Robert A. van de Geijn.
acm sigplan symposium on principles and practice of parallel programming (2009)

159 Citations

iMODS: internal coordinates normal mode analysis server

José Ramón López-Blanco;José Ignacio Aliaga;Enrique S. Quintana-Ortí;Pablo Chacón.
Nucleic Acids Research (2014)

145 Citations

SuperMatrix: a multithreaded runtime scheduling system for algorithms-by-blocks

Ernie Chan;Field G. Van Zee;Paolo Bientinesi;Enrique S. Quintana-Orti.
acm sigplan symposium on principles and practice of parallel programming (2008)

136 Citations

A complete and efficient CUDA-sharing solution for HPC clusters

Antonio J. Peña;Carlos Reaño;Federico Silla;Rafael Mayo.
parallel computing (2014)

125 Citations

Best Scientists Citing Enrique S. Quintana-Ortí

Jack Dongarra

Jack Dongarra

University of Tennessee at Knoxville

Publications: 156

Peter Benner

Peter Benner

Max Planck Institute for Dynamics of Complex Technical Systems

Publications: 94

Stanimire Tomov

Stanimire Tomov

University of Tennessee at Knoxville

Publications: 52

Robert A. van de Geijn

Robert A. van de Geijn

The University of Texas at Austin

Publications: 46

Rosa M. Badia

Rosa M. Badia

Barcelona Supercomputing Center

Publications: 38

Piotr Luszczek

Piotr Luszczek

University of Tennessee at Knoxville

Publications: 38

Eduard Ayguadé

Eduard Ayguadé

Barcelona Supercomputing Center

Publications: 33

Jesús Labarta

Jesús Labarta

Barcelona Supercomputing Center

Publications: 33

Xavier Martorell

Xavier Martorell

Barcelona Supercomputing Center

Publications: 24

Antonio Plaza

Antonio Plaza

University of Extremadura

Publications: 20

George Bosilca

George Bosilca

University of Tennessee at Knoxville

Publications: 16

James Demmel

James Demmel

University of California, Berkeley

Publications: 12

Pavan Balaji

Pavan Balaji

Argonne National Laboratory

Publications: 10

Dimitrios S. Nikolopoulos

Dimitrios S. Nikolopoulos

Virginia Tech

Publications: 10

Markus Püschel

Markus Püschel

ETH Zurich

Publications: 10

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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