The SISTEMIC group has four research areas:
We develop techniques and tools to transform models for their respective functional simulation and code generation for the design of HW / SW required in complex and robust embedded applications. Different methodologies and design paradigms such Model Driven Architectures (MDA), UML, SystemC and low-level languages for the synthesis of multicore platforms are considered. Our applications are focused in the areas of health, communications, transportation and energy.
High performance computing
We are interested in exploring new hardware and software techniques to achieve high performance computing systems that respect cost and power limitations, among others. One of the most important elements in our work is the parallel programming of homogeneous and heterogeneous architectures. We use multicores, GPUs and FPGAs in the search for an increased computing power and efficiency. Currently, we have projects that apply HPC techniques to solve computing problems in bioinformatics and neuroscience.
Digital Signal Processing
It includes the acquisition and processing of biological signals for diagnosis and treatment of diseases, identification of species of frogs and birds. We have applications in estimation and automation of large-scale, traffic and smart-grid energy systems; also we have worked on some security systems including biometric identification of people and automatic video analysis.
Development of techniques for monitoring complex processes using virtual robots to identify and predict online situations. For the construction of automatic pattern recognition and data analysis techniques, several fuzzy classification, RNA and SVM techniques are used. These have been applied in industrial processes, chemical reactors, steam generators, vehicles and telehealth support systems for monitoring chronic patients. For data analysis techniques other area of Computational Intelligence as RNA and SVM are included.