Parallel implementation of fuzzy minimals clustering algorithm

Clustering aims to classify different patterns into groups called clusters. Many algorithms for both hard and fuzzy clustering have been developed to deal with exploratory data analysis in many contexts such as image processing, pattern recognition, etc. However, we are witnessing the era of big data computing where computing resources are becoming the main bottleneck to deal with those large datasets. In this context, sequential algorithms need to be redesigned and even rethought to fully leverage the emergent massively parallel architectures. In this paper, we propose a parallel implementation of the fuzzy minimals clustering algorithm called Parallel Fuzzy Minimal (PFM). Our experimental results reveal linear speed-up of PFM when compared to the sequential counterpart version, keeping very good classification quality.Ingeniería, Industria y Construcció

METADOCK: A parallel metaheuristic schema for virtual screening methods

Virtual screening through molecular docking can be translated into an optimization problem, which can be tackled with metaheuristic methods. The interaction between two chemical compounds (typically a protein, enzyme or receptor, and a small molecule, or ligand) is calculated by using highly computationally demanding scoring functions that are computed at several binding spots located throughout the protein surface. This paper introduces METADOCK, a novel molecular docking methodology based on parameterized and parallel metaheuristics and designed to leverage heterogeneous computers based on heterogeneous architectures. The application decides the optimization technique at running time by setting a configuration schema. Our proposed solution finds a good workload balance via dynamic assignment of jobs to heterogeneous resources which perform independent metaheuristic executions when computing different molecular interactions required by the scoring functions in use. A cooperative scheduling of jobs optimizes the quality of the solution and the overall performance of the simulation, so opening a new path for further developments of virtual screening methods on high-performance contemporary heterogeneous platforms.Ingeniería, Industria y Construcció

METADOCK 2: a high-throughput parallel metaheuristic scheme for molecular docking

[EN] Motivation Molecular docking methods are extensively used to predict the interaction between protein-ligand systems in terms of structure and binding affinity, through the optimization of a physics-based scoring function. However, the computational requirements of these simulations grow exponentially with: (i) the global optimization procedure, (ii) the number and degrees of freedom of molecular conformations generated and (iii) the mathematical complexity of the scoring function. Results In this work, we introduce a novel molecular docking method named METADOCK 2, which incorporates several novel features, such as (i) a ligand-dependent blind docking approach that exhaustively scans the whole protein surface to detect novel allosteric sites, (ii) an optimization method to enable the use of a wide branch of metaheuristics and (iii) a heterogeneous implementation based on multicore CPUs and multiple graphics processing units. Two representative scoring functions implemented in METADOCK 2 are extensively evaluated in terms of computational performance and accuracy using several benchmarks (such as the well-known DUD) against AutoDock 4.2 and AutoDock Vina. Results place METADOCK 2 as an efficient and accurate docking methodology able to deal with complex systems where computational demands are staggering and which outperforms both AutoDock Vina and AutoDock 4.This work was partially supported by the Fundación Séneca del Centro de Coordinación de la Investigación de la Región de Murcia [Projects 20813/PI/ 18, 20988/PI/18, 20524/PDC/18] and by the Spanish Ministry of Science, Innovation and Universities [TIN2016-78799-P (AEI/FEDER, UE), CTQ2017-87974-R]. 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LEADS-PEP: A Benchmark Data Set for Assessment of Peptide Docking Performance. Journal of Chemical Information and Modeling, 56(1), 188-200. doi:10.1021/acs.jcim.5b00234Llanes, A., Muñoz, A., Bueno-Crespo, A., García-Valverde, T., Sánchez, A., Arcas-Túnez, F., … M. Cecilia, J. (2016). Soft Computing Techniques for the Protein Folding Problem on High Performance Computing Architectures. Current Drug Targets, 17(14), 1626-1648. doi:10.2174/1389450117666160201114028McIntosh-Smith, S., Price, J., Sessions, R. B., & Ibarra, A. A. (2014). High performance in silico virtual drug screening on many-core processors. The International Journal of High Performance Computing Applications, 29(2), 119-134. doi:10.1177/1094342014528252Mehler, E. L., & Solmajer, T. (1991). Electrostatic effects in proteins: comparison of dielectric and charge models. «Protein Engineering, Design and Selection», 4(8), 903-910. doi:10.1093/protein/4.8.903Morris, G. M., Goodsell, D. S., Halliday, R. S., Huey, R., Hart, W. 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Towards Energy Efficiency in Heterogeneous Processors: Findings on Virtual Screening Methods

The integration of the latest breakthroughs in computational modeling and high performance computing (HPC) has leveraged advances in the fields of healthcare and drug discovery, among others. By integrating all these developments together, scientists are creating new exciting personal therapeutic strategies for living longer that were unimaginable not that long ago. However, we are witnessing the biggest revolution in HPC in the last decade. Several graphics processing unit architectures have established their niche in the HPC arena but at the expense of an excessive power and heat. A solution for this important problem is based on heterogeneity. In this paper, we analyze power consumption on heterogeneous systems, benchmarking a bioinformatics kernel within the framework of virtual screening methods. Cores and frequencies are tuned to further improve the performance or energy efficiency on those architectures. Our experimental results show that targeted low‐cost systems are the lowest power consumption platforms, although the most energy efficient platform and the best suited for performance improvement is the Kepler GK110 graphics processing unit from Nvidia by using compute unified device architecture. Finally, the open computing language version of virtual screening shows a remarkable performance penalty compared with its compute unified device architecture counterpart.Ingeniería, Industria y Construcció

Metal Knitting: A New Strategy for Cold Gas Spray Additive Manufacturing

Cold Spray Additive Manufacturing (CSAM) is an emergent technique to produce parts by the additive method, and, like other technologies, it has pros and cons. Some advantages are using oxygen-sensitive materials to make parts, such as Ti alloys, with fast production due to the high deposition rate, and lower harmful residual stress levels. However, the limitation in the range of the parts' geometries is a huge CSAM con. This work presents a new conceptual strategy for CSAM spraying. The controlled manipulation of the robot arm combined with the proper spraying parameters aims to optimize the deposition efficiency and the adhesion of particles on the part sidewalls, resulting in geometries from thin straight walls, less than 5 mm thick, up to large bulks. This new strategy, Metal Knitting, is presented regarding its fundamentals and by comparing the parts' geometries produced by Metal Knitting with the traditional strategy. The Metal Knitting described here made parts with vertical sidewalls, in contrast to the 40 degrees of inclination obtained by the traditional strategy. Their mechanical properties, microstructures, hardness, and porosity are also compared for Cu, Ti, Ti6Al4V, 316L stainless steel, and Al

A Performance/Cost Evaluation for a GPU-Based Drug Discovery Application on Volunteer Computing

Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and, thus, the use of high performance computing (HPC) platforms is mandatory for the generation of useful biological knowledge. The latest generation of graphics processing units (GPUs) has democratized the use of HPC as they push desktop computers to cluster-level performance. Many applications within this field have been developed to leverage these powerful and low-cost architectures. However, these applications still need to scale to larger GPU-based systems to enable remarkable advances in the fields of healthcare, drug discovery, genome research, etc. The inclusion of GPUs in HPC systems exacerbates power and temperature issues, increasing the total cost of ownership (TCO). This paper explores the benefits of volunteer computing to scale bioinformatics applications as an alternative to own large GPU-based local infrastructures. We use as a benchmark a GPU-based drug discovery application called BINDSURF that their computational requirements go beyond a single desktop machine. Volunteer computing is presented as a cheap and valid HPC system for those bioinformatics applications that need to process huge amounts of data and where the response time is not a critical factor.Ingeniería, Industria y Construcció

A Performance/Cost Model for a CUDA Drug Discovery Application on Physical and Public Cloud Infrastructures

Virtual Screening (VS) methods can considerably aid drug discovery research, predicting how ligands interact with drug targets. BINDSURF is an efficient and fast blind VS methodology for the determination of protein binding sites, depending on the ligand, using the massively parallel architecture of graphics processing units(GPUs) for fast unbiased prescreening of large ligand databases. In this contribution, we provide a performance/cost model for the execution of this application on both local system and public cloud infrastructures. With our model, it is possible to determine which is the best infrastructure to use in terms of execution time and costs for any given problem to be solved by BINDSURF. Conclusions obtained from our study can be extrapolated to other GPU‐based VS methodologiesIngeniería, Industria y Construcció

Improving drug discovery using a neural networks based parallel scoring function

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface to find new hotspots, where ligands might potentially interact with, and which is implemented in massively parallel Graphics Processing Units, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to solve this problem, we propose a novel approach where neural networks are trained with databases of known active (drugs) and inactive compounds, and later used to improve VS predictions.This work has been jointly supported by the Fundación Séneca (Agencia Regional de Ciencia y Tecnología de la Región de Murcia) under grant 15290/PI/2010, by the Spanish MINECO and the European Commission FEDER funds under grants TIN2009-14475-C04 and TIN2012-31345, and by the Catholic University of Murcia (UCAM) under grant PMAFI/26/12. This work was partially supported by the computing facilities of Extremadura Research Centre for Advanced Technologies (CETA-CIEMAT), funded by the European Regional Development Fund (ERDF). CETA-CIEMAT belongs to CIEMAT and the Government of Spain

Soft Computing Techiniques for the Protein Folding Problem on High Performance Computing Architectures

The protein-folding problem has been extensively studied during the last fifty years. The understanding of the dynamics of global shape of a protein and the influence on its biological function can help us to discover new and more effective drugs to deal with diseases of pharmacological relevance. Different computational approaches have been developed by different researchers in order to foresee the threedimensional arrangement of atoms of proteins from their sequences. However, the computational complexity of this problem makes mandatory the search for new models, novel algorithmic strategies and hardware platforms that provide solutions in a reasonable time frame. We present in this revision work the past and last tendencies regarding protein folding simulations from both perspectives; hardware and software. Of particular interest to us are both the use of inexact solutions to this computationally hard problem as well as which hardware platforms have been used for running this kind of Soft Computing techniques.This work is jointly supported by the FundaciónSéneca (Agencia Regional de Ciencia y Tecnología, Región de Murcia) under grants 15290/PI/2010 and 18946/JLI/13, by the Spanish MEC and European Commission FEDER under grant with reference TEC2012-37945-C02-02 and TIN2012-31345, by the Nils Coordinated Mobility under grant 012-ABEL-CM-2014A, in part financed by the European Regional Development Fund (ERDF). We also thank NVIDIA for hardware donation within UCAM GPU educational and research centers.Ingeniería, Industria y Construcció

Desarrollo de una plataforma integral de servicios basicos - chamberos

El presente proyecto de investigación tiene como objetivo presentar el desarrollo de nuestra propuesta de negocio Chamberos, la cual se dedica a ofrecer diversos servicios de reparaciones como fontanería, electrodomésticos, construcción, etc. A través de una forma fácil y segura, por medio de un aplicativo, que lo ayudará a contactar con servicios para incidentes que se puedan presentar en sus hogares. Para dar a conocer sobre este nuevo emprendimiento contamos con dos canales, página web y redes sociales de esta formar lograr tener una comunicación directa con nuestros clientes. Es importante mencionar que los servicios brindados, se darán a través de la modalidad a domicilio, logrando que el cliente ahorre tiempo al momento de solicitar estos servicios, además que los recibirá en la comodidad de su hogar sin necesidad de salir. Para la validación de nuestra idea de negocio, se realizaron varias entrevistas y encuestas donde se obtuvieron las diferentes opiniones de usuarios y expertos acerca del aplicativo Chamberos, así como también elaboramos diversos experimentos, lo cual nos ayudó a determinar la aceptación de los usuarios peruanos con el aplicativo, además que validamos nuestras hipótesis planteadas en cada experimento. Por último, con la finalidad de determinar si el proyecto Chamberos es viable en el mercado peruano, se elaboró un plan financiero completo para determinar que si nuestra idea de negocio es sostenible en el tiempo proyectado de tres años. Con ello determinamos que el proyecto presentado Chamberos es viable, debido a que en nuestros resultados financieros contamos con rentabilidad.The objective of this research project is to present the development of our Chamberos business proposal, which is dedicated to offering various repair services such as plumbing, electrical appliances, construction, etc. Through an easy and safe way, through an application, which will help you contact services for incidents that may occur in your homes. To publicize about this new venture we have two channels, a website and social networks, in order to achieve direct communication with our clients. It is important to mention that the services provided will be given through the home mode, achieving that the client saves time when requesting these services, in addition to receiving them in the comfort of their home without having to leave. For the validation of our business idea, several interviews and surveys were carried out where the different opinions of users and experts about the Chamberos application were obtained, as well as we developed various experiments, which helped us determine the acceptance of Peruvian users with the application, in addition that we validate our hypotheses raised in each experiment. Finally, in order to determine if the Chamberos project is viable in the Peruvian market, a complete financial plan was prepared to determine whether our business idea is sustainable in the projected time of three years. With this we determine that the Chamberos project presented is viable, because in our financial results we have profitability.Trabajo de investigació