Demo Data from VLDB 2026 / reviewers in the wild / expert
José Colmenares
dblp:116/5316
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › molecular informatics › molecular modeling
molecular electrostatics |
0.2 | 1 | 2014 | GPU linear and non-linear Poisson-Boltzmann solver module for DelPhi · Bioinform. 2014 |
GPUs and heterogeneous computing
GPU computing |
0.1 | 1 | 2014 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | GPU linear and non-linear Poisson-Boltzmann solver module for DelPhiabstractSUMMARY: 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 CUDAabstractIn 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 |
PDP | 1 |