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 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.
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.
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.
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)
iMODS: internal coordinates normal mode analysis server
José Ramón López-Blanco;José Ignacio Aliaga;Enrique S. Quintana-Ortí;Pablo Chacón.
Nucleic Acids Research (2014)
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)
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)
Solving stable generalized Lyapunov equations with the matrix sign function
Peter Benner;Peter Benner;Enrique S. Quintana-Ortí.
Numerical Algorithms (1999)
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)
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)
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)
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)
The libflame Library for Dense Matrix Computations
Field G. Van Zee;Ernie Chan;Robert A. van de Geijn;Enrique S. Quintana-Ortí.
Computing in Science and Engineering (2009)
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