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José Colmenares

dblp:116/5316 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
GPUs and heterogeneous computing · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › molecular informatics › molecular modeling
molecular electrostatics
0.212014
GPU linear and non-linear Poisson-Boltzmann solver module for DelPhi · Bioinform. 2014
GPUs and heterogeneous computing
GPU computing
0.112014
GPU linear and non-linear Poisson-Boltzmann solver module for DelPhi · Bioinform. 2014

Methods — techniques the papers use, named apart from their topics

finite difference scheme · 0.4double precision · 0.4CUDA · 0.4
YearPublicationVenuePosition
2014 GPU linear and non-linear Poisson-Boltzmann solver module for DelPhi
abstract
SUMMARY: In this work, we present a CUDA-based GPU implementation of a Poisson-Boltzmann equation solver, in both the linear and non-linear versions, using double precision. A finite difference scheme is adopted and made suitable for the GPU architecture. The resulting code was interfaced with the electrostatics software for biomolecules DelPhi, which is widely used in the computational biology community. The algorithm has been implemented using CUDA and tested over a few representative cases of biological interest. Details of the implementation and performance test results are illustrated. A speedup of ~10 times was achieved both in the linear and non-linear cases. AVAILABILITY AND IMPLEMENTATION: The module is open-source and available at http://www.electrostaticszone.eu/index.php/downloads.
José Colmenares, Jesús Ortiz 0001, Walter Rocchia
Bioinform.1
2013 Solving the Linearized Poisson-Boltzmann Equation on GPUs Using CUDA
abstract
In this work an implementation of a linearized Poisson-Boltzmann equation solver based on a Finite Differences scheme on the GPU architecture is presented. The algorithm exploits the checkerboard structure of the discretized Laplace operator and follows the footprints of a popular solver called DelPhi, which is widely used in the Computational Biology community. The algorithm has been implemented using CUDA. This implementation has then been integrated with the DelPhi solver and tested over a few representative cases of biological interest. Details of the implementation as well as performance test results are illustrated.
José Colmenares, Jesús Ortiz 0001, Sergio Decherchi, Amir Fijany, Walter Rocchia
PDP1