Multicore Architecture-aware Scientific Applications

Modern high performance systems are becoming increasingly complex and powerful due to advancements in processor and memory architecture. In order to keep up with this increasing complexity, applications have to be augmented with certain capabilities to fully exploit such systems. These may be at the application level, such as static or dynamic adaptations or at the system level, like having strategies in place to override some of the default operating system polices, the main objective being to improve computational performance of the application. The current work proposes two such capabilites with respect to multi-threaded scientific applications, in particular a large scale physics application computing ab-initio nuclear structure. The first involves using a middleware tool to invoke dynamic adaptations in the application, so as to be able to adjust to the changing computational resource availability at run-time. The second involves a strategy for effective placement of data in main memory, to optimize memory access latencies and bandwidth. These capabilties when included were found to have a significant impact on the application performance, resulting in average speedups of as much as two to four times

Uma arquitetura paralela para o armazenamento de imagens médicas em sistemas de arquivos distribuídos

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência da Computação.Com a implantação da Rede Catarinense de Telemedicina tem-se verificado um aumento significativo no volume de imagens médicas, do padrão DICOM, geradas pelos dispositivos médicos interconectados nesta rede. Visando a manipulação dessas imagens médicas, foi desenvolvido em um projeto prévio, um servidor conhecido como CyclopsDCMServer, para a manipulação das imagens DICOM considerando a abordagem usando o Hierarchical Data Format (HDF5). Todavia, é esperado que a abordagem venha a encontrar gargalos devido ao crescimento no volume de dados e operações simultâneas que são submetidas ao servidor. Com o objetivo de dar continuidade ao esforço para prover uma melhor escalabilidade ao servidor CyclopsDCMServer, nesta dissertação apresenta-se uma pesquisa no sentido de potencializar a implementação de um paradigma paralelo no servidor para o armazenamento e recuperação das imagens DICOM. Desta forma, desenvolveu-se um módulo considerando bibliotecas E/S paralelas de alto desempenho. Este módulo efetua uma comunicação com o servidor que é responsável pela realização do acesso paralelo no formato de dados hierárquico. Visando a avaliação de desempenho da abordagem paralela, foram executados experimentos em diferentes sistemas de arquivos distribuídos. Os experimentos foram focados principalmente nas operações de armazenamento e recuperação das imagens médicas. Comparou-se o tempo médio de execução de cada operação em serial e paralelo. Foi coletado também o tempo de E/S em cada operação, para averiguar somente o desempenho do processo de escrita e leitura dos dados, descartando qualquer atraso que pudesse interferir nos resultados. Os resultados empíricos demonstraram que, independente do sistema de arquivos, a abordagem paralela ainda não apresenta uma eficiência considerável, quando comparada com a arquitetura serial. A média do declínio de desempenho pode ser considerada em torno de 45% na operação de recuperação e 71% na operação de armazenamento. Verificou-se também que o aumento do número de processos paralelos pode causar uma perda maior de desempenho nesta abordagem.With the deployment of Catarinense Network of Telemedicine has verified a meaningful increase in volume of medical images, DICOM standard, generated by medical devices interconnected on this network. In order to manipulate this medical images was develop in one previous project, a server known as CyclopsDCMServer, to manipulate DICOM images considering the approach Hierarchical Data Format (HDF5). However, it is expected that this approach will find bottlenecks due the spread of data size and simultaneously operations submitted to the server. With focus to continue the effort to supply better scalability to the server CyclopsDCMServer, this dissertation presents a research in the sense to empowerment the implementation of a parallel paradigm in the server to storage and retrieve DICOM images. Thus, it was developed a module considering high performance parallel I/O libraries. This module performs a communication with the server that is responsible for the creation of parallel access in hierarchical data format Aiming at the performance evaluation of the parallel approach, experiments were performed in different distributed file systems. The experiments were mainly focused on the operations of storage and retrieval of medical images. It was compared the average execution time of each operation in serial and parallel. It was also collected the I/O time in each operation, only to ascertain the performance of the process of writing and reading data, discarding any delay that could meddle the results. The empirical results show that, regardless of file system, the parallel approach does not present a considerable eficiency when compared to the serial architecture. The average decline in performance can be seen at around 45 % in the recovery operation and 71 % in the storage operation. It was also observed that increasing the number of parallel processes can cause a larger loss of performance in this approach

Benefits of Parallel I/O in Ab Initio Nuclear Physics Calculations, ICCS 2009 Proceedings

Many modern scientific applications rely on highly parallel calculations, which scale to 10's of thousands processors. However, most applications do not concentrate on parallelizing input/output operations. In particular, sequential I/O has been identified as a bottleneck for the highly scalable MFDn (Many Fermion Dynamics for nuclear structure) code performing ab initio nuclear structure calculations. In this paper, we develop interfaces and parallel I/O procedures to use a well-known parallel I/O library in MFDn. As a result, we gain efficient input/output of large datasets along with their portability and ease of use in the downstream processing