Computer-aided programming for multiprocessing systems

As both the number of processors and the complexity of problems to be solved increase, programming multiprocessing systems becomes more difficult and error-prone. This report discusses parallel models of computation and tools for computer-aided programming (CAP). Program development tools are necessary since programmers are not able to develop complex parallel programs efficiently. In particular, a CAP tool, named Hypertool, is described here. It performs scheduling and handles the communication primitive insertion automatically so that many errors are eliminated. It also generates the performance estimates and other program quality measures to help programmers in improving their algorithms and programs. Experiments have shown that up to a 300% performance improvement can be achieved by computer-aided programming

MPI-dot2dot: A Parallel Tool to Find DNA Tandem Repeats on Multicore Clusters

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] Tandem Repeats (TRs) are segments that occur several times in a DNA sequence, and each copy is adjacent to other. In the last few years, TRs have gained significant attention as they are thought to be related with certain human diseases. Therefore, identifying and classifying TRs have become a highly important task in bioinformatics in order to analyze their disorders and relationships with illnesses. Dot2dot, a tool recently developed to find TRs, provides more accurate results than the previous state-of-the-art, but it requires a long execution time even when using multiple threads. This work presents MPI-dot2dot, a novel version of this tool that combines MPI and OpenMP so that it can be executed in a cluster of multicore nodes and thus reduces its execution time. The performance of this new parallel implementation has been tested using different real datasets. Depending on the characteristics of the input genomes, it is able to obtain the same biological results as Dot2dot but more than 100 times faster on a 16-node multicore cluster (384 cores). MPI-dot2dot is publicly available to download from https://sourceforge.net/projects/mpi-dot2dot.This work was supported by the Ministry of Science and Innovation of Spain (PID2019-104184RB-I00 / AEI / 10.13039/501100011033), and by Xunta de Galicia and FEDER funds (Centro de Investigación de Galicia accreditation 2019-2022 and Consolidation Program of Competitive Reference Groups, under Grants ED431G 2019/01 and ED431C 2021/30, respectively). The authors would like to thank the Galician Supercomputing Center (CESGA) for providing access to the Finis Terrae II supercomputer. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer NatureXunta de Galicia; ED431G 2019/01Xunta de Galicia; ED431C 2021/3

Paralelization of Genetic Algorithms

Tato práce se zabývá možností paralelizace Genetického Algoritmu a jeho ná-sledné evaluace pomocí testovacích účelových funkcí. První část je teoretická a shrnuje základní poznatky z oblasti Genetických Algoritmů, paralelních archi-tektur, paralelních výpočtů a optimalizace. A dále je tato část doplněna o mož-nosti paralelizace Genetického Algoritmu. V následující praktické části je rozebrán algoritmus paralelního Genetického Algoritmu, jenž je použitý při experimentu a také je diskutována struktura a účel zvoleného experimentu. Následně jsou diskutovány výsledky získané z běhu experimentu na Eridani Clusteru z pohledu zrychlení výpočtu, kvality nalezeného řešení a závislosti kvality řešení na migračním schématu.This thesis deals with Genetic Algorithm parallelization and its evaluation. The theoretical part of the thesis describes the basics of Genetic Algorithms, parallel architectures, parallel computing and optimization, followed by the description of possibility to parallelize Genetic Algorithm. In practical part, the implementation of parallel Genetic Algorithm is discussed as well as design of experiment for the best evaluation by means of testing fitness functions. Subsequently the results obtained from the experiment on Eridani Cluster are evaluated in terms of speed up, the quality of solution and dependency on migration scheme used.

A Parallel implementation of an mpeg-2 encoder using message-passing

The days of film are waning as digital cameras and digital video cameras are becoming commonplace. Uncompressed digital video can consume large amounts of space, making it cumbersome to store efficiently. A method of video compression was developed by the Motion Pictures Expert Group (MPEG), and is now an international standard with the International Organization for Standardization (ISO). This thesis deals with the MPEG-2 Video standard, ISO/IEC 13818-2 [2]. The goal of this thesis is to explore the applications of MPEG-2 encoding in a parallel processing paradigm. To achieve this, a sequential MPEG-2 software encoder was obtained from the MPEG Software Simulation Group (MSSG) [18] and modified to be run, in parallel, on a cluster of single-processor Linux workstations using the Message Passing Interface (MPI) [11, 10, 3]. A multi-threaded pipeline of the encoding process was created using Pthreads [6]. The resulting pipelined parallel encoder has been shown to produce compliant elementary MPEG-2 bitstreams for progressive video sequences. Results of simulation showed that the parallel encoder always performed better than the sequential version as the number of processors scaled. However, it did not exhibit the ideal linear speedup that all parallel programs aim to achieve. This is due to the program executing on a set of resources not ideal for the multi-threaded pipeline. The ensuing chapters will provide the motivation for this work, and an overview of MPEG in addition to parallel processing and programming. Also forthcoming will be how it was achieved and the results produced. Supplementary applications of this work will also be discussed