Prototipado de sistemas multiprocesador en FPGA

Los procesadores tradicionales de un solo núcleo han tenido que enfrentarse a grandes desafíos para poder mejorar su rendimiento y eficiencia energética. Mientras tanto, el rápido avance de las tecnologías de fabricación ha permitido la implementación de varios procesadores en un solo chip, ofreciendo un alto rendimiento y eficiencia energética. Éstos son los llamados procesadores multinúcleo. El objetivo de este proyecto es realizar un sistema multiprocesador para el procesamiento digital de señales de radio. Este sistema multiprocesador puede ser implementado en una tarjeta de prototipado. Para ello se ha utilizado el softcore MB-Lite y el sistema operativo en tiempo real FreeRTOS. ABSTRACT. Traditional single-core processors have faced great challenges to improve their performance and energy efficiency. Meanwhile, rapid advancing fabrication technologies have enabled the implementation of several processors in a single chip, providing high performance and energy efficiency. These are called multi-core processors. The aim of this project is to perform a multiprocessor system for digital radio signal processing. This multiprocessor system can be implemented in a general purpose prototyping card using. To achieve this project, the MB-Lite softcore and the FreeRTOS real time operating system have been used.

Efficient parallelization of a regional ocean model for the western Mediterranean Sea

This paper focuses on the parallelization of an ocean model applying current multicore processor-based cluster architectures to an irregular computational mesh. The aim is to maximize the efficiency of the computational resources used. To make the best use of the resources offered by these architectures, this parallelization has been addressed at all the hardware levels of modern supercomputers: firstly, exploiting the internal parallelism of the CPU through vectorization; secondly, taking advantage of the multiple cores of each node using OpenMP; and finally, using the cluster nodes to distribute the computational mesh, using MPI for communication within the nodes. The speedup obtained with each parallelization technique as well as the combined overall speedup have been measured for the western Mediterranean Sea for different cluster configurations, achieving a speedup factor of 73.3 using 256 processors. The results also show the efficiency achieved in the different cluster nodes and the advantages obtained by combining OpenMP and MPI versus using only OpenMP or MPI. Finally, the scalability of the model has been analysed by examining computation and communication times as well as the communication and synchronization overhead due to parallelization.