# Gloria Ortega LopezUniversity of Malaga | UMA · Department of Computers Architecture

Gloria Ortega Lopez

Computer Science

## About

56

Publications

12,297

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391

Citations

Introduction

Additional affiliations

June 2009 - July 2016

## Publications

Publications (56)

Adders are one of the most interesting circuits in quantum computing due to their use in major algorithms that benefit from the special characteristics of this type of computation. Among these algorithms, Shor's algorithm stands out, which allows decomposing numbers in a time exponentially lower than the time needed to do it with classical computat...

Quantum image processing focuses on the use of quantum computing in the field of digital image processing. In the last few years, this technique has emerged since the properties inherent to quantum mechanics would provide the computing power required to solve hard problems much faster than classical computers. Binarization is often recognized to be...

Modern computational platforms are characterized by the heterogeneity of their processing elements. Additionally, there are many algorithms which can be structured as a set of procedures or tasks with different computational cost. Balancing the computational load among the available processing elements is one of the main keys for the optimal exploi...

Reversible adders are essential circuits in quantum computing systems. They are a fundamental part of the algorithms implemented for such systems, where Shor's celebrated factoring algorithm is one of the most prominent examples in which reversible arithmetic is needed. There is a wide variety of works in the existing literature which tackle the de...

Despite the great interest that the scientific community has in quantum computing, the scarcity and high cost of resources prevent to advance in this field. Specifically, qubits are very expensive to build, causing the few available quantum computers are tremendously limited in their number of qubits and delaying their progress. This work presents...

Despite the great interest that the scientific community has in quantum computing, the scarcity and high cost of resources prevent to advance in this field. Specifically, qubits are very expensive to build, causing the few available quantum computers are tremendously limited in their number of qubits and delaying their progress. This work presents...

The analysis of the dynamics of tracer particles in a complex bath can provide valuable information about the microscopic behavior of the bath. In this work, we study the dynamics of a forced tracer in a colloidal bath by means of Langevin dynamics simulations and a theory model within continuum mechanics. In the simulations, the bath is comprised...

The analysis of the dynamics of tracer particles in a complex bath can provide valuable information about the microscopic behaviour of the bath. In this work, we study the dynamics of a forced tracer in a colloidal bath by means of Langevin dynamics simulations and a theory model within continuum mechanics. In the simulations, the bath is comprised...

Current teaching guides of Computer Engineering degrees include the learning of digital systems that perform operations using binary variables. Logical gates are the simplest cases of these digital systems. They allow to produce a binary output from one or more binary inputs.
This paper proposes a methodology, like the one currently used in digita...

Nowadays, one of the critical issues to implement quantum algorithms is the required number of elementary gates, qubits and delay. Current quantum computers and simulators are mainly prototypes, and there is a lack of computational resources. Therefore, it is necessary to optimize the quantum operations to reduce the necessary number of gates and q...

Quantum computers are emerging as one of the most novels technologies nowadays. These computers work through quantum circuits which, unlike classic computer circuits, follow the set of rules determined by quantum mechanics. However, those rules are counterintuitive, and it is necessary to define appropriate techniques to explain them to students. T...

Maintenance costs account for a large part of the total cost of an offshore wind farm. Several models have been presented in the literature to optimize the fleet composition of the required vessels to support maintenance tasks. We provide a mixed integer linear programming (MILP) description of such a model, where on the higher level, the fleet com...

The reduction of the dimensionality is of great interest in the context of big data processing. Multidimensional scaling methods (MDS) are techniques for dimensionality reduction, where data from a high-dimensional space are mapped into a lower-dimensional space. Such methods consume relevant computational resources; therefore, intensive research h...

Dynamic programming (DP) approaches, in particular value iteration, is often seen as a method to derive optimal policies in inventory management. The challenge in this approach is to deal with an increasing state space when handling realistic problems. As a large part of world food production is thrown out due to its perishable character, a motivat...

As a large part of world food production spoils/expires before consumption, reduction of food waste by optimizing order policies in retail is of importance. We sketch here the computational burden of trying to obtain the optimal order quantities with the process of Value Iteration for a retailer situation with highly perishable products. It appears...

The isometric mapping (Isomap) algorithm is often used for analysing hyperspectral images. Isomap allows to reduce such hyperspectral images from a high-dimensional space into a lower-dimensional space, keeping the critical original information. To achieve such objective, Isomap uses the state-of-the-art MultiDimensional Scaling method (MDS) for di...

Quantum computers base their operations on optimized circuit designs. These quantum circuits, unlike classic circuits, follow the set of rules determined by quantum mechanics. Currently, one of the main problems to solve in Quantum Computation is Shor’s algorithm, which consists in factoring large numbers. It is based on arithmetic operations, ther...

Dynamic programming (DP) is often seen in inventory control to lead to optimal ordering policies. When considering stationary demand, Value Iteration (VI) may be used to derive the best policy. In this paper, our focus is on the computational procedures to implement VI. Practical implementation requires bounding carefully the state space and demand...

Active microrheology has emerged in recent years as a new technique to probe microscopically the mechanical properties of materials, particularly, viscoelastic ones. In this technique, a colloidal tracer is pulled through the material, and its dynamics is monitored. The interpretation of results usually relies on the Stokes–Einstein approximation,...

Quantum computers base their operations on an optimized circuit design. These quantum circuits, unlike classic circuits, follow the set of rules determined by quantum mechanics. Nowadays, it is a challenge to obtain optimized circuits, even for the simplest operations, due to the scarcity of resources of the current quantum computers. A basic opera...

Una gran parte de la producción mundial de alimentos se desecha debido a su carácter pere-cedero. Esto hace que exista una gran motivación para investigar las políticas óptimas de pedidos de productos perecederos en el comercio minorista que minimicen las grandes cantidades de alimentos que van a la basura. En este trabajo analizamos los aspectos c...

Non-Dominated Sorting (NDS) is the most time-consuming procedure used in the majority of evolutionary multiobjective optimization algorithms that are based on Pareto dominance ranking without regard to the computation time of the objective functions. It can be accelerated by the exploitation of its parallelism on High Performance Computing systems,...

The reduction of the dimensionality is of great interest in the context of big data processing. Multidimensional scaling methods (MDS) are techniques for dimensionality reduction, where data from a high-dimensional space are mapped into a lower-dimensional space. Such methods consume relevant computational resources; therefore, intensive research h...

Evolutionary multi-objective optimization algorithms aim at finding an approximation of the Pareto set. For hard to solve problems with many conflicting objectives, the number of functions evaluations to represent the Pareto front can be large and time consuming. Parallel computing can reduce the wall-clock time of such algorithms. Previous studies...

Maintenance provides a large part of the cost of an offshore wind farm. Several models have been presented in literature to optimize the fleet composition of the required vessels. A drawback such models is that they are based on perfect information on weather and incidences to schedule for the coming year. Our research question is what will happen...

The offshore wind energy industry is expected to continue its growth tendency in the near future. The European Wind Energy Association expects in its Central Scenario by 2030 a total installed capacity of 66 GW of offshore wind in the UE. Offshore wind farms (OWFs) are large scale infrastructures, requiring maintenance fleets to perform operations...

We present a discrete optimisation model that chooses an optimal fleet of vessels to support maintenance operations at Offshore Wind Farms (OFWs). The model is presented as a bi-level problem. On the first (tactical) level, decisions are made on the fleet composition for a certain time horizon. On the second (operational) level, the fleet is used t...

This paper analyses and evaluates parallel implementations of an optimization algorithm for perishable inventory control problems. This iterative algorithm has high computational requirements when solving large problems. Therefore, the use of parallel and distributed computing reduces the execution time and improves the quality of the solutions. Th...

Last generation supercomputers running bioinformatics workloads are composed of multiple heterogeneous processing units, requiring intelligent workload distribution. This paper describes an accurate static workload balancing model capable of (i) efficiently balancing the workload with no significant overhead because only a static light off-line pro...

Nowadays, the application of Evolutionary Multi-Objective Optimization (EMO) algorithms in real-time systems receives considerable interest. In this context, the energy efficiency of computational systems is of paramount relevance. Recently, the use of embedded systems based on heterogeneous (CPU + GPU) platforms is consistently increasing. For exa...

Complex fluids are characterized with both solid and fluid properties by their elasticity and viscosity, or rheological behaviour. The flow of complex fluids is a focus of interest in a very wide range of applications in biophysics and soft matter, such as problems involving live cells, processing of plastic, glass, paints, foods, oil recovery and...

Problems for which many objective functions have to be simultaneously optimized can be easily found in many fields of science and industry. Solving this kind of problems in a reasonable amount of time while taking into account the energy efficiency is still a relevant task. Most of the evolutionary multi-objective optimization algorithms based on p...

Active microrheology is a technique to obtain rheological properties in soft matter from the microscopic motion of colloidal tracers used as probes and subjected to external forces. This technique extends the measurement of the friction coefficient to the nonlinear-response regime of strongly driven probes. Active microrheology can be described sta...

Computer Science is advancing rapidly and it is ne- cessary to keep the educational resources up to date in order to keep the interest of students. Nowadays, there is a wide variety of low-cost computing platforms that are used as educational resources in the Computer Science degree. Raspberry Pi and some models of Arduino (such as Arduino Due), wh...

En este trabajo se analizan y evalúan dos implementaciones de un algoritmo de optimización para un problema de control de inventarios de productos perecederos. Las implementaciones se han llevado a cabo utilizando una arquitectura heterogénea donde cada nodo está compuesto por varios multicores y varias GPUs. Las versiones paralelas que se han desa...

Optical Diffraction Tomography has been recently introduced in fluid velocimetry to provide three dimensional information of seeding particle locations. In general, image reconstruction methods at visible wavelengths have to account for diffraction. Linear approximation has been used for three-dimensional image reconstruction, but a non-linear and...

Programmers usually implement iterative methods that solve partial differential equations by expressing them using a sequence of basic kernels from libraries optimized for the graphics processing unit (GPU). The global runtime of the resulting combination is often penalized by the smallest and most inefficient vector operations. To improve the GPU...

The detection of mesoscale oceanic structures, such as upwellings or eddies, from satellite images has significance for marine environmental studies, coastal resource management, and ocean dynamics studies. Nevertheless, there is a lack of tools that allow us to retrieve automatically relevant mesoscale structures from large satellite image databas...

Tomography has been recently introduced in fluid velocimetry to provide three dimensional information of the location of particles. In particular, author’s previous works have proven the potential of Optical Diffraction Tomography for biological and microfluidic devices. In general, image reconstruction methods at visible wavelengths have to accoun...

The resolution of the 3D Helmholtz equation is required in the development of models related to a wide range of scientific and technological applications. For solving this equation in complex arithmetic, the biconjugate gradient (BCG) method is one of the most relevant solvers. However, this iterative method has a high computational cost because of...

We are interested in the resolution of the 3D Helmholtz equation for real applications. Solving this problem numerically is a computational challenge due to the large memory requirements of the matrices and vectors involved.For these cases, the massive parallelism of GPU architectures and the high performance at lower energy of the multicores can b...

Sparse matrix matrix (SpMM) multiplication is involved in a wide range of scientific and technical applications. The computational
requirements for this kind of operation are enormous, especially for large matrices. This paper analyzes and evaluates a method
to efficiently compute the SpMM product in a computing environment that includes graphics p...

In a wide variety of applications from different scientific and engineering fields, the solution of complex and/or nonsymmetric linear systems of equations is required. To solve this kind of linear systems the BiConjugate Gradient method (BCG) is especially relevant. Nevertheless, BCG has a enormous computational cost. GPU computing is useful for a...

A wide range of applications in engineering and
scientific computing are based on the computation of matrices
products, where one of them is sparse. The computational
requirements of these operations are very high when dimensions
of the matrices increase. The goal of this work is the acceleration
of the sparse matrix matrix product (SpMM) on Graphi...

This paper analyses several parallel approaches for the development of a physical model of Non-linear ODT for its application in velocimetry techniques. The main benefits of its application in HPIV are the high accuracy with non-damaging radiation and its imaging capability to recover information from the vessel wall of the flow. Thus ODT-HPIV is s...

Sparse matrices are involved in linear systems, eigensystems and partial differential equations from a wide spectrum of scientific and engineering disciplines. Hence, sparse matrix vector product (SpMV) is considered as key operation in engineering and scientific computing. For these applications the optimization of the sparse matrix vector product...

## Questions

Questions (3)

Could anybody tell me applications (or bibliography links) in which it is neccessary to solve a multiobjective problem with populations larger or equal to 100,000 individuals?

I have designed a High Performance routine for computing the Sparse

Matrix Matrix Product based on CUDA and I would like to knew the interest of this operation in different fields.

Thank you!.

I have designed a High Performance routine for computing the Sparse Matrix Matrix Product based on CUDA and I would like to knew the interest of this operation in different fields.

Thank you!

## Projects

Projects (2)

So far my investigation lead to insights in (dynamic) decision making on many topics: experimental design, deforestation, production scheduling, water management, logistic handling, farm management, mixture design, fishery management, maintenance, water systems investment, traffic control, inventory control, location decisions, emission trading, windfarm design, unmixing hyperspectral data, CPU process scheduling, supply chain design, coalition formation etc.
The focus is on using specific characteristics (theorems) of optimization models to develop specific algorithms to solve them. In this search, many solution methods for dynamic optimization and global optimization are confronted with high computational effort. The next question is how parallel computing using high performance computing can be used to solve challenging problems for this world.