Fine grain software pipelining of non-vectorizable nested loops

This paper presents a new technique to parallelize nested loops at the statement level. It transforms sequential nested loops, either vectorizable or not, into parallel ones. Previously, the wavefront method was used to parallelize non-vectorizable nested loops. However, in order to reduce the complexity of parallelization, the wavefront method regards an iteration as an unbreakable scheduling unit and draws parallelism through iteration overlapping. Our technique takes a statement rather than an iteration as the scheduling unit and exploits parallelism by overlapping the statements in all dimensions. In this paper, we show how this finer grain parallelization can be achieved with reasonable computational complexity, and the effectiveness of the resulting method in exploiting parallelism

N-Dimensional Perfect Pipelining

In this paper, we introduce a technique to parallelize nested loops at the fine grain level. It is a generalization of Perfect Pipelining which was developed to parallelize a single-nested loop at the fine grain level. Previous techniques that can parallelize nested loops, e.g. DOACROSS or Wavefront method, mostly belong to the coarse grain approach. We explain our method, contrast it with the coarse grain techniques, and show the benefits of parallelizing nested loops at the fine grain level

Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS

GROMACS is a widely used package for biomolecular simulation, and over the last two decades it has evolved from small-scale efficiency to advanced heterogeneous acceleration and multi-level parallelism targeting some of the largest supercomputers in the world. Here, we describe some of the ways we have been able to realize this through the use of parallelization on all levels, combined with a constant focus on absolute performance. Release 4.6 of GROMACS uses SIMD acceleration on a wide range of architectures, GPU offloading acceleration, and both OpenMP and MPI parallelism within and between nodes, respectively. The recent work on acceleration made it necessary to revisit the fundamental algorithms of molecular simulation, including the concept of neighborsearching, and we discuss the present and future challenges we see for exascale simulation - in particular a very fine-grained task parallelism. We also discuss the software management, code peer review and continuous integration testing required for a project of this complexity.Comment: EASC 2014 conference proceedin

Silicon compilation

Silicon compilation is a term used for many different purposes. In this paper we define silicon compilation as a mapping from some higher level description into layout. We define the basic issues in structural and behavioral silicon compilation and some possible solutions to those issues. Finally, we define the concept of an intelligent silicon compiler in which the compiler evaluates the quality of the generated design and attempts to improve it if it is not satisfactory

Speculative parallelism in Intel Cilk Plus

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 37).Certain algorithms can be effectively parallelized at the cost of performing some redundant work. One example is searching an unordered tree graph for a particular node. Each subtree can be searched in parallel by a separate thread. Once a single thread is successful, however, the work of the others is unneeded and should be ended. This type of computation is known as speculative parallelism. Typically, an abort command is provided in the programming language to provide this functionality, but some languages do not. This thesis shows how support for the abort command can be provided as a user-level library. A parallel version of the alpha beta search algorithm demonstrates its effectivenesss.by Ruben Perez.M.Eng

A Novel Compiler Support for Automatic Parallelization on Multicore Systems

[Abstract] The widespread use of multicore processors is not a consequence of significant advances in parallel programming. In contrast, multicore processors arise due to the complexity of building power-efficient, high-clock-rate, single-core chips. Automatic parallelization of sequential applications is the ideal solution for making parallel programming as easy as writing programs for sequential computers. However, automatic parallelization remains a grand challenge due to its need for complex program analysis and the existence of unknowns during compilation. This paper proposes a new method for converting a sequential application into a parallel counterpart that can be executed on current multicore processors. It hinges on an intermediate representation based on the concept of domain-independent kernel (e.g., assignment, reduction, recurrence). Such kernel-centric view hides the complexity of the implementation details, enabling the construction of the parallel version even when the source code of the sequential application contains different syntactic variations of the computations (e.g., pointers, arrays, complex control flows). Experiments that evaluate the effectiveness and performance of our approach with respect to state-of-the-art compilers are also presented. The benchmark suite consists of synthetic codes that represent common domain-independent kernels, dense/sparse linear algebra and image processing routines, and full-scale applications from SPEC CPU2000.[Resumen] El uso generalizado de procesadores multinúcleo no es consecuencia de avances significativos en programación paralela. Por el contrario, los procesadores multinúcleo surgen debido a la complejidad de construir chips mononúcleo que sean eficiente energéticamente y tengan altas velocidades de reloj. La paralelización automática de aplicaciones secuenciales es la solución ideal para hacer la programación paralela tan fácil como escribir programas para ordenadores secuenciales. Sin embargo, la paralelización automática continua a ser un gran reto debido a su necesidad de complejos análisis del programa y la existencia de incógnitas durante la compilación. Este artículo propone un nuevo método para convertir una aplicación secuencial en su contrapartida paralela que pueda ser ejecutada en los procesadores multinúcleo actuales. Este método depende de una representación intermedia basada en el concepto de núcleos independientes del dominio (p. ej., asignación, reducción, recurrencia). Esta visión centrada en núcleos oculta la complejidad de los detalles de implementación, permitiendo la construcción de la versión paralela incluso cuando el código fuente de la aplicación secuencial contiene diferentes variantes de las computaciones (p. ej., punteros, arrays, flujos de control complejos). Se presentan experimentos que evalúan la efectividad y el rendimiento de nuestra aproximación con respecto al estado del arte. La serie programas de prueba consiste en códigos sintéticos que representan núcleos independientes del dominio comunes, rutinas de álgebra lineal densa/dispersa y de procesamiento de imagen, y aplicaciones completas del SPEC CPU2000.[Resumo] O uso xeralizado de procesadores multinúcleo non é consecuencia de avances significativos en programación paralela. Pola contra, os procesadores multinúcleo xurden debido á complexidade de construir chips mononúcleo que sexan eficientes enerxéticamente e teñan altas velocidades de reloxo. A paralelización automática de aplicacións secuenciais é a solución ideal para facer a programación paralela tan sinxela como escribir programas para ordenadores secuenciais. Sen embargo, a paralelización automática continua a ser un gran reto debido a súa necesidade de complexas análises do programa e a existencia de incógnitas durante a compilación. Este artigo propón un novo método para convertir unha aplicación secuencias na súa contrapartida paralela que poida ser executada nos procesadores multinúcleo actuais. Este método depende dunha representación intermedia baseada no concepto dos núcleos independentes do dominio (p. ex., asignación, reducción, recurrencia). Esta visión centrada en núcleos oculta a complexidade dos detalles de implementación, permitindo a construcción da versión paralela incluso cando o código fonte da aplicación secuencial contén diferentes variantes das computacións (p. ex., punteiros, arrays, fluxos de control complejo). Preséntanse experimentos que evalúan a efectividade e o rendemento da nosa aproximación con respecto ao estado da arte. A serie de programas de proba consiste en códigos sintéticos que representan núcleos independentes do dominio comunes, rutinas de álxebra lineal densa/dispersa e de procesamento de imaxe, e aplicacións completas do SPEC CPU2000.Ministerio de Economía y Competitividad; TIN2010-16735Ministerio de Educación y Cultura; AP2008-0101

Metaheuristic approaches for optimal broadcasting design in metropolitan MANETs

11th International Conference on Computer Aided Systems Theory. Las Palmas de Gran Canaria, Spain, February 12-16, 2007Mobile Ad-hoc Networks (MANETs) are composed of a set of communicating devices which are able to spontaneously interconnect without any pre-existing infrastructure. In such scenario, broadcasting becomes an operation of tremendous importance for the own existence and operation of the network. Optimizing a broadcasting strategy in MANETs is a multiobjective problem accounting for three goals: reaching as many stations as possible, minimizing the network utilization, and reducing the duration of the operation itself. This research, which has been developed within the OPLINK project (http://oplink.lcc.uma.es), faces a wide study about this problem in metropolitan MANETs with up to seven different advanced multiobjective metaheuristics. They all compute Pareto fronts of solutions which empower a human designer with the ability of choosing the preferred configuration for the network. The quality of these fronts is evaluated by using the hypervolume metric. The obtained results show that the SPEA2 algorithm is the most accurate metaheuristic for solving the broadcasting problem.Publicad