In the last decade the multicore processors had emerged with the comeback of the symmetric multiprocessing (SMP) after a long decade in which the based OpenMPI clusters had dominated the high performace processing world. Actually, we have in the market 2, 4 and 6 multicore processors; the Cell BE processors with a Power Processor Element (PPE) and 8 vectorial processors called Synergistic Processor Element (SPE), and graphics processors which have from 48 to 448 cores dedicated to numerical tasks. In the present work, we show our experience in the interaction with these processors, discussing the programming techniques and the future possibilities for making low cost numerical tasks.

The resolution of triangular systems is a computational nucleus widely used in various scientific applications. This research performs the implementation and comparison of several parallel algorithms against an efficient sequential algorithm for solving triangular systems. The algorithms are distinguished by the way of partitioning the matrix and the allocation to the processors. The analysis of the behavior of the algorithms is performed in the solution of systems of linear superior triangular equations in a cluster of computers. For this, the arithmetic time, communication time, speed-up, and maximum efficiency metrics are taken into account. Experiments were performed for each algorithm with different matrix sizes on various processors. The algorithm with the best results was the one that blocks the rows of the matrix and applies a cyclical distribution in the cluster.

Nowadays, some of the most popular tools for parallel programming are Message Passing Interface and Open Multi-Processing. It is of interest to compare these tools in solving the same kind of problems, because of the use of different approaches to inter-task communication. This work attempts to contribute to this goal by running trials in a centralized shared memory architecture in the case of problems with an entirely parallel solution. The selected case study was the parallel computation of Mandelbrot set. Trials were conducted for different iteration limits, processors amount, and C++ implementation variants. The results show better performance in the case of Open Multi-Processing.

In recent years, the number of applications of model predictive control (MPC) is rapidly increasing due to the better control performance that it provides in comparison to traditional control methods. However, the main limitation of MPC is the computational e ort required for the online solution of an optimization problem. This shortcoming restricts the use of MPC for real-time control of dynamic systems with high sampling rates. This thesis aims to overcome this limitation by implementing high-performance MPC solvers for real-time control of fast systems. Hence, one of the objectives of this work is to take the advantage of the particular mathematical structures that MPC schemes exhibit and use parallel computing to improve the computational e ciency. Firstly, this thesis focuses on implementing e cient parallel solvers for linear MPC (LMPC) problems, which are described by block-struct...

In recent years, the number of applications of model predictive control (MPC) is rapidly increasing due to the better control performance that it provides in comparison to traditional control methods. However, the main limitation of MPC is the computational e ort required for the online solution of an optimization problem. This shortcoming restricts the use of MPC for real-time control of dynamic systems with high sampling rates. This thesis aims to overcome this limitation by implementing high-performance MPC solvers for real-time control of fast systems. Hence, one of the objectives of this work is to take the advantage of the particular mathematical structures that MPC schemes exhibit and use parallel computing to improve the computational e ciency. Firstly, this thesis focuses on implementing e cient parallel solvers for linear MPC (LMPC) problems, which are described by block-struct...

In recent years, the number of applications of model predictive control (MPC) is rapidly increasing due to the better control performance that it provides in comparison to traditional control methods. However, the main limitation of MPC is the computational e ort required for the online solution of an optimization problem. This shortcoming restricts the use of MPC for real-time control of dynamic systems with high sampling rates. This thesis aims to overcome this limitation by implementing high-performance MPC solvers for real-time control of fast systems. Hence, one of the objectives of this work is to take the advantage of the particular mathematical structures that MPC schemes exhibit and use parallel computing to improve the computational e ciency. Firstly, this thesis focuses on implementing e cient parallel solvers for linear MPC (LMPC) problems, which are described by block-struct...

This article develops a robust platform for remote process management.JAVA language is used as a programming language at three levels of development: Control Servers, Web Server and Web Clients. The interaction with the control servers will be through the serial port and/or parallel port depending on the requirement. Thus we can interact with any specialized control device: A microcontroller, a PLC (Programmable Logic Controller), a DSP (Digital Signal Processor) or sophisticated sensors that send data through the aforementioned ports, theLocal network of Control servers ensure the reliability and proper functioning of our processes.The exit door to the Internet will be the "Web Servers", which serve clients; Such a client does not have direct access to the system, until it has verified its privileges. The information thatjourney through the Web is encrypted. Using a microcontroller we w...