A new parallel overlapped domain decomposition method for nonlinear dynamic finite element analysis

In this paper a new parallel algorithm for nonlinear transient dynamic analysis of large structures has been presented. An unconditionally stable Newmark-beta method (constant average acceleration technique) has been employed for time integration. The proposed parallel algorithm has been devised within the broad framework of domain decomposition techniques. However, unlike most of the existing parallel algorithms (devised for structural dynamic applications) which are basically derived using nonoverlapped domains, the proposed algorithm uses overlapped domains. The parallel overlapped domain decomposition algorithm proposed in this paper has been formulated by splitting the mass, damping and stiffness matrices arises out of finite element discretisation of a given structure. A predictor-corrector scheme has been formulated for iteratively improving the solution in each step. A computer program based on the proposed algorithm has been developed and implemented with message passing interface as software development environment. PARAM-10000 MIMD parallel computer has been used to evaluate the performances. Numerical experiments have been conducted to validate as well as to evaluate the performance of the proposed parallel algorithm. Comparisons have been made with the conventional nonoverlapped domain decomposition algorithms. Numerical studies indicate that the proposed algorithm is superior in performance to the conventional domain decomposition algorithms. (C) 2003 Elsevier Ltd. All rights reserved.

Extensiones multimedia Intel

Desde que se inventó el primer ordenador, uno de los objetivos ha sido que el ordenador fuese capaz de ejecutar más y más rápido, para poder así solucionar problemas más complejos. La primera solución fue aumentar la potencia de los procesadores, pero las limitaciones físicas impuestas por la velocidad de los componentes electrónicos han obligado a buscar otras formas de mejorar el rendimiento. Desde entonces, ha habido muchos tipos de tecnologías para aumentar el rendimiento como los multiprocesadores, las arquitecturas MIMD… pero nosotros analizaremos la arquitectura SIMD. Este tipo de procesadores fue muy usado en los supercomputadores de los años 80 y 90, pero el progreso de los microprocesadores hizo que esta tecnología quedara en un segundo plano. Hoy en día la todos los procesadores tienen arquitecturas que implementan las instrucciones SIMD (Single Instruction, Multiple Data). En este documento estudiaremos las tecnologías de SIMD de Intel SSE, AVX y AVX2 para ver si realmente usando el procesador vectorial con las instrucciones SIMD, se obtiene alguna mejora de rendimiento. Hay que tener en cuenta que AVX solo está disponible desde 2011 y AVX2 no ha estado disponible hasta el 2013, por lo tanto estaremos trabajando con nuevas tecnologías. Además este tipo de tecnologías tiene el futuro asegurado, al anunciar Intel su nueva tecnología, AVX- 512 para 2015.

An Operating Environment for the Jellybean Machine

The Jellybean Machine is a scalable MIMD concurrent processor consisting of special purpose RISC processors loosely coupled into a low latency network. I have developed an operating system to provide the supportive environment required to efficiently coordinate the collective power of the distributed processing elements. The system services are developed in detail, and may be of interest to other designers of fine grain, distributed memory processing networks.

FPGA based Soft-core SIMD Processing: A MIMO-OFDM Fixed-Complexity Sphere Decoder Case Study

To enable reliable data transfer in next generation Multiple-Input Multiple-Output (MIMO) communication systems, terminals must be able to react to fluctuating channel conditions by having flexible modulation schemes and antenna configurations. This creates a challenging real-time implementation problem: to provide the high performance required of cutting edge MIMO standards, such as 802.11n, with the flexibility for this behavioural variability. FPGA softcore processors offer a solution to this problem, and in this paper we show how heterogeneous SISD/SIMD/MIMD architectures can enable programmable multicore architectures on FPGA with similar performance and cost as traditional dedicated circuit-based architectures. When applied to a 4×4 16-QAM Fixed-Complexity Sphere Decoder (FSD) detector we present the first soft-processor based solution for real-time 802.11n MIMO.

Concurrent Aggregates (CA): An Object-Oriented Language for Fine-Grained Message-Passing Machines

Fine-grained parallel machines have the potential for very high speed computation. To program massively-concurrent MIMD machines, programmers need tools for managing complexity. These tools should not restrict program concurrency. Concurrent Aggregates (CA) provides multiple-access data abstraction tools, Aggregates, which can be used to implement abstractions with virtually unlimited potential for concurrency. Such tools allow programmers to modularize programs without reducing concurrency. I describe the design, motivation, implementation and evaluation of Concurrent Aggregates. CA has been used to construct a number of application programs. Multi-access data abstractions are found to be useful in constructing highly concurrent programs.

Concurrent Smalltalk on the Message-Driven Processor

Concurrent Smalltalk is the primary language used for programming the J- Machine, a MIMD message-passing computer containing thousands of 36-bit processors connected by a very low latency network. This thesis describes in detail Concurrent Smalltalk and its implementation on the J-Machine, including the Optimist II global optimizing compiler and Cosmos fine-grain parallel operating system. Quantitative and qualitative results are presented.

Parallel matrix inversion techniques

In this paper, we present techniques for inverting sparse, symmetric and positive definite matrices on parallel and distributed computers. We propose two algorithms, one for SIMD implementation and the other for MIMD implementation. These algorithms are modified versions of Gaussian elimination and they take into account the sparseness of the matrix. Our algorithms perform better than the general parallel Gaussian elimination algorithm. In order to demonstrate the usefulness of our technique, we implemented the snake problem using our sparse matrix algorithm. Our studies reveal that the proposed sparse matrix inversion algorithm significantly reduces the time taken for obtaining the solution of the snake problem. In this paper, we present the results of our experimental work.

Estudo do efeito de máscara e do efeito terapêutico de dois colutórios na redução da halitose

Dissertação para obtenção do grau de Mestre no Instituto Superior de Ciências da Saúde Egas Moniz