From CeCal - High Performance Computing

Main: Research

The HPC group has been involved in numerous research activities, whose details are briefly presented below.

Research projects (some websites in Spanish)

2016:

Currently in progress.
To be available: https://www.fing.edu.uy/inco/grupos/cecal/hpc/AEIA
Currently in progress.
To be available: https://www.fing.edu.uy/inco/grupos/cecal/hpc/RFRE
Currently in progress.
To be available: https://www.fing.edu.uy/inco/grupos/cecal/hpc/DRCC
Currently in progress.
To be available: https://www.fing.edu.uy/inco/grupos/cecal/hpc/IOTU

2015:

Available at: https://www.fing.edu.uy/inco/grupos/cecal/hpc/APMP
Available at: https://www.fing.edu.uy/inco/grupos/cecal/hpc/PPSH
We study scheduling algorithms for large workflows in distributed datacenters.
Information available: EAWSDD

2014:

The project proposes a study about drivers on public roads in order to detect patterns of reckless driving through footage in real time. A study on pattern recognition in traffic patterns will be performed. The ultimate goal is develop a software product to generate alerts to detect patterns of reckless driving. These alerts will be shown in video comparison.
Partners: Universidad de la República (Uruguay).
Information available: https://www.fing.edu.uy/inco/grupos/cecal/hpc/DPT/
This project proposes the study of the problem of public transport planning by synchronizing traffic lights and design and implementation of an evolutionary algorithm to solve numerical computational performance and high efficiency.
Partners: Universidad de la República (Uruguay).
Information available: https://www.fing.edu.uy/inco/grupos/cecal/hpc/AECG/
The project proposes applying HPC/distributed computing techniques over cluster and cloud computing platforms for studying cell biology processes.
Partners: Universidad de la República (Uruguay), Universidad de Buenos Aires (Argentina).
Information available: http://www.fing.edu.uy/inco/grupos/cecal/hpc/CCED
The project presents the application of parallel micro evolutionary algorithms for solving the problem of distributing a group of passengers travelling from the same origin to different destinations in several taxis.
Information available: http://www.fing.edu.uy/inco/grupos/cecal/hpc/AG-Taxi

2013:

The project proposes to improve the behavior of MapReduce-based applications on pervasive grids and desktop grids
Partners: Université de Reims Champagne-Ardenne (France), Universidad de la República (Uruguay), Universidade Federal de Santa Maria (Brasil), Université Paris 1 – Panthéon Sorbonne (France)
Information available: http://cosy.univ-reims.fr/PER-MARE
The project proposes to develop runtime systems that combine application characteristics with topology information to automatically offer scheduling hints that try to respect hardware and software affinities.
Partners: Runtime group, INRIA Bordeaux-Sud-Ouest, France (local coordinator Brice Goglin), High Performance Computing Group, Universidad de la República, Uruguay (local coordinator Sergio Nesmachnow), LIDIC laboratory, Universidad Nacional de San Luis (local coordinator Marcela Printista).
Information available: http://runtime.bordeaux.inria.fr/sehloc/
The project study efficient allocation algorithms for of a set of customers virtual machine requests into available pre-booked resources from a cloud broker, in order to maximize the broker profit..
Information available: http://www.fing.edu.uy/inco/grupos/cecal/hpc/VMMP
The project proposes the design and implementation of energy-aware scheduling algorithms for heterogeneous computing systems.
Information available: http://www.fing.edu.uy/inco/grupos/cecal/hpc/MScIturriaga
The project proposes the use of soft computing techniques implemented over high performance computing infrastructures to solve image processing problems.
Information available: http://www.fing.edu.uy/inco/grupos/cecal/hpc/SCHPC-IP
The project proposes designing a parallel neural network approach implemented over Graphic Processing Units (GPU) to solve a facial recognition problem, which consists in deciding where the face of a person in a certain image is pointing. The proposed method uses the parallel capabilities of GPU in order to train and evaluate a neural network used to solve the aforementioned problem.
Information available: http://www.fing.edu.uy/inco/grupos/cecal/hpc/ANN-FR
The project proposes using high performance computing techniques for efficient and accurate computing the self-gravity of granular solar system bodies (asteroids, comets, etc.).
Information available (in Spanish): http://www.fing.edu.uy/inco/grupos/cecal/hpc/HPCGM
The project consists in designing a greedy resource allocation policy for OurGrid middleware in heterogeneous scenarios. The main purpose is the reduction of the makespan of jobs submitted by users.
Information available: http://www.fing.edu.uy/inco/grupos/cecal/hpc/GSOS
The aim of the Digi-Clima project is to provide semi-automatic processing capabilities for historical graphical rain intensity records. A stable version of the algorithm is available, but new features are under development. Digi-Clima been developed since early 2011 and by mid-2011 a running version was already available. The Digi-Clima application was conceived as a script written in Matlab-compatible language and should run with no problems using Matlab or Octave.
Information available: http://www.fing.edu.uy/inco/grupos/cecal/hpc/digiclima
The project characterizes the computational efficiency behavior of a standard evolutionary algorithm as a software program. The experimental analysis allows concluding that significant improvemets in efficiency can be gained by applying simple guidelines on how to best program an evolutionary algorithm.
Information available: http://www.fing.edu.uy/inco/grupos/cecal/hpc/ETAEASP

2012:

The project implements and analyzes efficent multiobjective evolutionary algorithms for scheduling in large heterogeneous computing systems.
Information available (in Spanish): http://www.fing.edu.uy/inco/grupos/cecal/hpc/MO-HCSP

2011:

The objective of GISELA is to ensure the long-term sustainability of the European–Latin American (EU-LA) e-Infrastructure, thus guaranteeing the continuity and the expected enhancement of the EU-LA Virtual Research Communities. The project focuses on two inter-related goals: i) implement the Latin American Grid Initiative (LGI) rooted on National Grid Initiatives (NGI)1, and ii) provide the Communities with the suited e-Infrastructure and Application-related Services required to improve the effectiveness of their research.
Information available: project website
The project proposes using high performance computing techniques for designing efficient and accurate algorithms for granular media simulations.
Information available (in Spanish): http://www.fing.edu.uy/inco/grupos/cecal/hpc/PMG
Cluster FING is the high performance scientific computing infrastructure in Facultad de Ingeniería. It has been used in nearly 50 research projects from Universidad de la República. The design, administration and operation of cluster FING is done by people from the HPC group at CeCal.
Information available: Cluster FING website
This project intends to design and implement efficent methods for scheduling in large heterogeneous computing systems, able to perform the planning in reduced times (i.e., less than a minute). The main concerns are the efficiency, accuracy and scalability of the studied methods.
Information available: http://www.fing.edu.uy/inco/grupos/cecal/hpc/HCSP

2010:

The project studies the application of parallel computing techniques to the recovery of historical climate data.

2009:

The project studies the application of parallel quantum computing algorithms for solving the 3-SAT problem.
EELA-2 aims at i) building a powerful, functional and well supported grid facility by expanding the e-Infrastructure in 41 Resource centers (13 in Europe and 28 in Latin America), by building the support of the e-Infrastructure to provide high reliability services to partnerships, and creating a comprehensive knowledge repository on Grid operation; ii) addressing a large community of users; iii) asserting the financial & management schemes to operate and support the e-Infrastructure on the long range; and iv) anticipating the handover of the e-Infrastructure operation and support.
Information available: project website
MOE is an object oriented framework for use of evolutionary algorithms in the resolution of multiobjective optimization problems..
Information available: http://www.fing.edu.uy/inco/grupos/cecal/hpc/MOE/

2008:

The project proposes the application of parallel evolutionary algorithms for solving the scheduling problem in large heterogenous clusters and grid environments. Information available: project website (in English)
The project proposes the application of parallel multiobjective evolutionary algorithms for solving the scheduling problem in large heterogenous clusters and grid environments. Information available: project website (in Spanish), project report (in Spanish).

2007:

The project proposes the application of evolutionary algorithms for solving the phylogenetic tree reconstruction problem. Information available: project website (in Spanish)
The main objective of this project is to design and implement an interface for the high performance cluster Medusa.
The project's goal is the implementation of a radiosity algorithm for fixed geometry and variable light scenarios, with a complexity order of nxm, (n is the number of patches and m<<n), running on a Cuda GPU architecture. The expected results includes the development of a code that works in real time (30 frames per second) with 10,000 patches scenes and with the hardware available.
The project proposes the implementation of a high performance cluster for solving complex numerical simulation models related to free surface flows problems.

2006:

The project proposes the implementation of a high performance cluster for solving applications with high CPU requirements. Information available: project website (in Spanish), project report (in Spanish), project website (in Spanish), technical report: performance evaluation (pdf, in Spanish)

2005:

The project proposed to apply high performance techniques to improve the computational efficiency of the RMA-10 shallow water model. Information available: project website (in Spanish), Master thesis (pdf, in Spanish).
This project was an international cooperation with Universidad Nacional de la Patagonia San Juan Bosco, Argentina. Its main objectives involved studying the frequency assignment problems in wireless networks and the aplicability of parallel genetic algorithms to solve real-size scenarios. Information available: project website (in Spanish), graduate thesis (pdf, in Spanish), research article (pdf).

2004:

The project present the design and implementation of a parallel version of the multiobjective evolutionary algorithm NSGA-II and its application to reliable communication network design. Information available: project website (in Spanish, it includes software, documentation, test instances and results), technical report (pdf, in Spanish).

2003:

2002:

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