Load Balancing Scientific Applications

The largest supercomputers have millions of independent processors, and concurrency levels are rapidly increasing. For ideal efficiency, developers of the simulations that run on these machines must ensure that computational work is evenly balanced among processors. Assigning work evenly is challenging because many large modern parallel codes simulate behavior of physical systems that evolve over time, and their workloads change over time. Furthermore, the cost of imbalanced load increases with scale because most large-scale scientific simulations today use a Single Program Multiple Data (SPMD) parallel programming model, and an increasing number of processors will wait for the slowest one at the synchronization points. To address load imbalance, many large-scale parallel applications use dynamic load balance algorithms to redistribute work evenly. The research objective of this dissertation is to develop methods to decide when and how to load balance the application, and to balance it effectively and affordably. We measure and evaluate the computational load of the application, and develop strategies to decide when and how to correct the imbalance. Depending on the simulation, a fast, local load balance algorithm may be suitable, or a more sophisticated and expensive algorithm may be required. We developed a model for comparison of load balance algorithms for a specific state of the simulation that enables the selection of a balancing algorithm that will minimize overall runtime. Dynamic load balancing of parallel applications becomes more critical at scale, while also being expensive. To make the load balance correction affordable at scale, we propose a lazy load balancing strategy that evaluates the imbalance and computes the new assignment of work to processes asynchronously to the main application computation. We decouple the load balance algorithm from the application and run it on potentially fewer, separate processors. In this Multiple Program Multiple Data (MPMD) configuration, the load balance algorithm can execute concurrently with the application and with higher parallel efficiency than if it were run on the same processors as the simulation. Work is reassigned lazily as directions become available, and the application need not wait for the load balance algorithm to complete. We show that we can save resources by running a load balance algorithm at higher parallel efficiency on a smaller number of processors. Using our framework, we explore the trade-offs of load balancing configurations and demonstrate a performance improvement of up to 46%

Multi-level load balancing for parallel particle simulations

Ideas from multi-level relaxation methods are combined with load balancing techniques to achieve a convergence acceleration for a homogeneous work load distribution over a given set of processors when the underlying work function is inhomogeneously distributed in space. The algorithm is based on an orthogonal recursive bisection ap- proach which is evaluated via a hierarchically refined coarse integration. The method only requires a minimal information transfer across processors during the tree traversal steps. It is described of how to partition the system of processors to geometrical space, when global information is needed for the spatial tesselation

A parallel implementation of an off-lattice individual-based model of multicellular populations

As computational models of multicellular populations include ever more detailed descriptions of biophysical and biochemical processes, the computational cost of simulating such models limits their ability to generate novel scientific hypotheses and testable predictions. While developments in microchip technology continue to increase the power of individual processors, parallel computing offers an immediate increase in available processing power. To make full use of parallel computing technology, it is necessary to develop specialised algorithms. To this end, we present a parallel algorithm for a class of off-lattice individual-based models of multicellular populations. The algorithm divides the spatial domain between computing processes and comprises communication routines that ensure the model is correctly simulated on multiple processors. The parallel algorithm is shown to accurately reproduce the results of a deterministic simulation performed using a pre-existing serial implementation. We test the scaling of computation time, memory use and load balancing as more processes are used to simulate a cell population of fixed size. We find approximate linear scaling of both speed-up and memory consumption on up to 32 processor cores. Dynamic load balancing is shown to provide speed-up for non-regular spatial distributions of cells in the case of a growing population

Implicit schemes and parallel computing in unstructured grid CFD

The development of implicit schemes for obtaining steady state solutions to the Euler and Navier-Stokes equations on unstructured grids is outlined. Applications are presented that compare the convergence characteristics of various implicit methods. Next, the development of explicit and implicit schemes to compute unsteady flows on unstructured grids is discussed. Next, the issues involved in parallelizing finite volume schemes on unstructured meshes in an MIMD (multiple instruction/multiple data stream) fashion are outlined. Techniques for partitioning unstructured grids among processors and for extracting parallelism in explicit and implicit solvers are discussed. Finally, some dynamic load balancing ideas, which are useful in adaptive transient computations, are presented

Computer Science Research Institute 2004 annual report of activities.

This report summarizes the activities of the Computer Science Research Institute (CSRI) at Sandia National Laboratories during the period January 1, 2004 to December 31, 2004. During this period the CSRI hosted 166 visitors representing 81 universities, companies and laboratories. Of these 65 were summer students or faculty. The CSRI partially sponsored 2 workshops and also organized and was the primary host for 4 workshops. These 4 CSRI sponsored workshops had 140 participants--74 from universities, companies and laboratories, and 66 from Sandia. Finally, the CSRI sponsored 14 long-term collaborative research projects and 5 Sabbaticals

A design method for supporting the development and integration of ARTful global schedulers into multiple programming models

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2019.Plataformas de execução em ambientes de alto desempenho estão tornando-se cada vez mais diversas com o desenvolvimento de novas arquiteturas e ferramentas para se beneficiar do paralelismo inerente das aplicações. Estas novas opções de ferramentas oferecem possibilidades de melhoria no desempenho de aplicações científicas e de engenharia. A crescente gama de plataformas torna mais complexa a distribuição das tarefas da aplicação no ambiente, passo que deve ser gerido pelos sistemas de execução e seus balanceadores de carga, de modo a não prejudicar a portabilidade da aplicação. No entanto, o desenvolvimento e implantação de novos escalonadores de tarefas em sistemas amplamente utilizados na indústria como OpenMP e MPI sofrem com a falta de suporte de frameworks. Este trabalho propõe uma biblioteca, MOGSLib, para auxiliar o desenvolvimento e implantação de escalonadores globais em diferentes sistemas de execução de alto desempenho. MOGSLib aplica abstrações reutilizáveis, independentes e testáveis na forma de classes template em C++ para representar as políticas de escalonamento, sua relação com o sistema de execução e a taxonomia da solução de escalonamento. Nós avaliamos o sobrecusto de nossas estratégias portáveis em comparação com suas versões nativas nos sistemas de execução em dois ambientes distintos, os sistemas Charm++ e OpenMP. Em nosso experimentos, conseguimos dar suporte à definição de estratégias de escalonamento do usuário e sua implantação como escalonadores de laço na LibGOMP e balanceadores de carga no Charm++ através da seleção de implementação das abstrações que os compõem. Nós verificamos que nossas versões dos escalonadores oferecem tempos de execução de aplicação equivalentes aos balanceadores nativos para a classe de escalonadores centralizados e cientes de carga aplicados em kernels de dinâmica molecular. Por fim, a flexibilidade de incorporar funcionalidades e políticas de escalonamento do usuário em sistemas de execução com modificações limitadas nos códigos de sistemas de execução mostra que é possível construir balanceadores de carga flexíveis com pouco sobrecusto até para ambientes de alto desempenho.Abstract: Execution platforms for high performance computing are becoming diverse as a result of new architectures and tools to benefit from the parallel behavior of applications. These new options showcase performance enhancing opportunities for scientific and engineering applications. The execution platform diversity and the mapping of an application's tasks must be implicitly handled by runtime systems and their global schedulers as to enable the application performance and implementation portability. However, the development and integration of novel global schedulers into industry standards systems like OpenMP and MPI lack framework support. This work proposes a library, MOGSLib, to support the development and integration of global schedulers into different high performance runtime systems. MOGSLib employs reusable, independent and testable abstractions represented as C++ template structures to express scheduling policies, their relationship to runtime systems and the scheduling solution taxonomy. This approach allows a bottom-up development process based on the incremental composition of abstractions through template specializations. We evaluate the overhead of employing our portable policies in comparison to their system-native counterparts in two environments, the Charm++ and OpenMP systems. Throughout our experiments we achieved development support for user-defined scheduling policies that can be implanted both as loop schedulers in LibGOMP and load balancers in Charm++ through the selection of abstraction implementations. We leveraged the overhead by employing workload-aware policies on molecular dynamics kernels which resulted in equivalent application makespan for both native and the MOGSLib scheduler versions. Ultimately, the flexibility to incorporate user-defined structures and scheduling policies into runtime systems with limited alterations into runtime system code bases hint that the definition of flexible global schedulers is available with neglible overheads even for high performance environments

Space Decomposition Based Parallelisation Solutions for the Combined Finite-Discrete Element Method in 2D.

PhDThe Combined Finite-Discrete Element Method (FDEM), originally invented by Munjiza, has become a tool of choice for problems of discontinua, where particles are deformable and can fracture or fragment. The downside of FDEM is that it is CPU intensive and, as a consequence, it is difficult to analyse large scale problems on sequential CPU hardware and parallelisation becomes necessary. In this work a novel approach for parallelisation of the combined finite-discrete element method (FDEM) in 2D aimed at clusters and desktop computers is developed. Dynamic domain decomposition-based parallelisation solvers covering all aspects of FDEM have been developed. These have been implemented into the open source Y2D software package by using a Message-Passing Interface (MPI) and have been tested on a PC cluster. The overall performance and scalability of the parallel code has been studied using numerical examples. The state of the art, the proposed solvers and the test results are described in the thesis in detail.

Parallel generalized Delaunay mesh refinement

The modeling of physical phenomena in computational fracture mechanics, computational fluid dynamics and other fields is based on solving systems of partial differential equations (PDEs). When PDEs are defined over geometrically complex domains, they often do not admit closed form solutions. In such cases, they are solved approximately using discretizations of domains into simple elements like triangles and quadrilaterals in two dimensions (2D), and tetrahedra and hexahedra in three dimensions (3D). These discretizations are called finite element meshes. Many applications, for example, real-time computer assisted surgery, or crack propagation from fracture mechanics, impose time and/or mesh size constraints that cannot be met on a single sequential machine. as a result, the development of parallel mesh generation algorithms is required.;In this dissertation, we describe a complete solution for both sequential and parallel construction of guaranteed quality Delaunay meshes for 2D and 3D geometries. First, we generalize the existing 2D and 3D Delaunay refinement algorithms along with theoretical proofs of mesh quality in terms of element shape and mesh gradation. Existing algorithms are constrained by just one or two specific positions for the insertion of a Steiner point inside a circumscribed disk of a poorly shaped element. We derive an entire 2D or 3D region for the selection of a Steiner point (i.e., infinitely many choices) inside the circumscribed disk. Second, we develop a novel theory which extends both the 2D and the 3D Generalized Delaunay Refinement methods for the concurrent and mathematically guaranteed independent insertion of Steiner points. Previous parallel algorithms are either reactive relying on implementation heuristics to resolve dependencies in parallel mesh generation computations or require the solution of a very difficult geometric optimization problem (the domain decomposition problem) which is still open for general 3D geometries. Our theory solves both of these drawbacks. Third, using our generalization of both the sequential and the parallel algorithms we implemented prototypes of practical and efficient parallel generalized guaranteed quality Delaunay refinement codes for both 2D and 3D geometries using existing state-of-the-art sequential codes for traditional Delaunay refinement methods. On a heterogeneous cluster of more than 100 processors our implementation can generate a uniform mesh with about a billion elements in less than 5 minutes. Even on a workstation with a few cores, we achieve a significant performance improvement over the corresponding state-of-the-art sequential 3D code, for graded meshes