Hierarchical Grid Research Articles

Unified Field Theory and the Hierarchical Universe

Everything from the smallest particle to the grand universe is constructed by Torque Grids. The grand structure of the universe is made up of infinite hierarchical Torque Grids; this theory falsifies Big Bang Theory (BBT) and Black Hole Theory. A Torque Grid is 10-25 times smaller than an atom, and our universal Torque Grid size is 4.98 * 1026 m. The Universe is timeless. The configuration of Spiral Arm Galaxy can also be explained by Unified Field Theory.

Research on Economic Grid Resource Scheduling for Utility Optimization

As Grid technologies evolve quickly on Internet, research related to resource scheduling faces new opportunities and challenges. These new technologies, ideas and approaches provide a new environment for researching and developing the economy-based resource scheduling system. Aiming at the hierarchical Grid model, following utility optimization thinking, while an universal flexible utility function is provided for addressing the Grid users’ QoS requirements of deadline and budget, this paper proposes a new Grid resource scheduling algorithm, which can not only increase the utilization of resources and system throughput, but also realize cost-time optimization between resource providers and users within Grid systems. On the basis of having described the different functional parts of the proposed algorithm, two kinds of simulative experiments about completion time and cost of tasks are conducted. Finally, the experiment results show that the proposed algorithm is effective.

A Parallel Auxiliary Grid Algebraic Multigrid Method for Graphic Processing Units

In this paper, we develop a new parallel auxiliary grid algebraic multigrid (AMG) method to leverage the power of graphic processing units (GPUs). In the construction of the hierarchical coarse grid, we use a simple and fixed coarsening procedure based on a region quadtree generated from an auxiliary grid. This allows us to explicitly control the sparsity patterns and operator complexities of the AMG solver. This feature provides (nearly) optimal load balancing and predictable communication patterns on shape regular grids, which makes our new algorithm suitable for parallel computing, especially on GPUs. We also design a parallel smoother based on the special coloring of the quadtree to accelerate the convergence rate and improve the parallel performance of this solver. Based on the CUDA toolkit [NVIDIA CUDA Programming Guide, NVIDIA Corp., 2010], we implemented our new parallel auxiliary grid AMG method on GPUs and the numerical results of this implementation demonstrate the efficiency of our new method ...

Improvement of Service Discovery Algorithm Using Tree-based Architecture in Ad-hoc Grid Environment

Grid computing is a new technology that using communication infrastructure facilities of computer networks and distributed systems features are able to connect to heterogeneous computing resources, so that the whole structure seems as an integrated virtual machine. One of the important problems in ad hoc grid environment is service discovery. In this paper, we propose tree directory architecture for service discovery in ad hoc grid environment, So that we used directory technique for implement of service discovery mechanism. We’ll show that having a directory in ad hoc gird network isn’t useful, so we need to have a set of directories. Therefore, the geographical area of ad hoc network divide into a 2-D logical hierarchical grid and each cell in the grid, select a directory as agent cell. By using tree architecture, the whole directory is designed as a multi-layer tree. Then, the request of requestor can be search for service discovery from bottom to top. We show using the simulation results that tree architecture for directories to raise the discovery success ratio.

A Novel Approach of Service Discovery Based on Tree Di-Rectory Architecture in Ad-Hoc Grid

Grid computing is a new technology that using communication infrastructure facilities of computer networks and distributed systems features are able to connect to heterogeneous computing resources, so that the whole structure seems as an integrated virtual machine. One of the important problems in ad hoc grid environment is service discovery. In this paper, we propose tree directory architecture for service discovery in ad hoc grid environment, So that we used directory technique for implement of service discovery mechanism. We’ll show that having a directory in ad hoc gird network isn’t useful, so we need to have a set of directories. Therefore, the geographical area of ad hoc network divide into a 2-D logical hierarchical grid and each cell in the grid, select a directory as agent cell. By using tree architecture, the whole directory is designed as a multi-layer tree. Then, the request of requestor can be search for service discovery from bottom to top. We show using the simulation results that tree architecture for directories to raise the discovery success ratio.

Parallel multigrid on hierarchical hybrid grids: a performance study on current high performance computing clusters

SUMMARYThis article studies the performance and scalability of a geometric multigrid solver implemented within the hierarchical hybrid grids (HHG) software package on current high performance computing clusters up to nearly 300,000 cores. HHG is based on unstructured tetrahedral finite elements that are regularly refined to obtain a block‐structured computational grid. One challenge is the parallel mesh generation from an unstructured input grid that roughly approximates a human head within a 3D magnetic resonance imaging data set. This grid is then regularly refined to create the HHG grid hierarchy. As test platforms, a BlueGene/P cluster located at Jülich supercomputing center and an Intel Xeon 5650 cluster located at the local computing center in Erlangen are chosen. To estimate the quality of our implementation and to predict runtime for the multigrid solver, a detailed performance and communication model is developed and used to evaluate the measured single node performance, as well as weak and strong scaling experiments on both clusters. Thus, for a given problem size, one can predict the number of compute nodes that minimize the overall runtime of the multigrid solver. Overall, HHG scales up to the full machines, where the biggest linear system solved on Jugene had more than one trillion unknowns. Copyright © 2012 John Wiley & Sons, Ltd.

Generating families of 3D periodic orbits about asteroids

The general three-dimensional periodic orbits around asteroids were investigated to study orbital behaviours in the vicinity of irregular gravitational bodies. The orbital patterns around periodic orbits were determined through decomposition into corresponding local manifolds. In this paper, a topological classification of periodic orbits is presented to discriminate the stability and dynamical behaviours of neighbours. A hierarchical grid searching method was developed for systematically searching three-dimensional periodic orbits around irregular bodies. The method was used to generate 29 basic families around the asteroid 216 Kleopatra as an example. By calculating the characteristic multipliers of periodic orbits, numerical evidence was generated to describe the denseness of periodic orbits around asteroids and to demonstrate the remarkable asymmetry among these orbits. The dependence of the topology of the periodic orbits on the Jacobi integral was examined, revealing the evolutionary features of the stability and orbital patterns nearby. The results can be used to assess the environment around 216 Kleopatra, and this method can be useful in the studies of other asteroids.

Hierarchical genetic-based grid scheduling with energy optimization

An optimization of power and energy consumptions is the important concern for a design of modern-day and future computing and communication systems. Various techniques and high performance technologies have been investigated and developed for an efficient management of such systems. All these technologies should be able to provide good performance and to cope under an increased workload demand in the dynamic environments such as Computational Grids (CGs), clusters and clouds.In this paper we approach the independent batch scheduling in CG as a bi-objective minimization problem with makespan and energy consumption as the scheduling criteria. We use the Dynamic Voltage Scaling (DVS) methodology for scaling and possible reduction of cumulative power energy utilized by the system resources. We develop two implementations of Hierarchical Genetic Strategy-based grid scheduler (Green-HGS-Sched) with elitist and struggle replacement mechanisms. The proposed algorithms were empirically evaluated versus single-population Genetic Algorithms (GAs) and Island GA models for four CG size scenarios in static and dynamic modes. The simulation results show that proposed scheduling methodologies fairly reduce the energy usage and can be easily adapted to the dynamically changing grid states and various scheduling scenarios.

Dynamic Replication Based on Availability and Popularity in the Presence of Failures

The data grid provides geographically distributed resources for large-scale applications. It generates a large set of data. The replication of this data in several sites of the grid is an effective solution for achieving good performance. In this paper we propose an approach of dynamic replication in a hierarchical grid that takes into account crash failures in the system. The replication decision is taken based on two parameters: the availability and popularity of the data. The administrator requires a minimum rate of availability for each piece of data according to its access history in previous periods, but this availability may increase if the demand is high on this data. We also proposed a strategy to keep the desired availability respected even in case of a failure or rarity (no- popularity) of the data. The simulation results show the effectiveness of our replication strategy in terms of response time, the unavailability of requests, and availability

Load Balancing in Optical Grids

This collaboration of geographically distributed domains in multi-domain optical grid environment should be done in a way that maintains the privacy of each participant domain. This calls for a new load balancing hierarchical approach to deal with such environments. In this paper, we propose two load balancing techniques within this hierarchical approach: Network Aware Divisible Load Algorithm (NADLA) and Genetic Algorithm based Load Distribution (GA-LD). Both algorithms are considered as Network Aware. Simulation results show the scalability and feasibility of the proposed approach and the advantages of the two proposed techniques compared to the classical Divisible Load Algorithm (DLA). In the last years, the growing of the scientific and enterprise applications pushes grid systems to more scalable and collaborative direction. Single domain resources are becoming insufficient to deal with application requirements. Grid applications require massive amounts of data to be transferred and processed in geographically distributed sites across the grid. The grid is an inter- connected multi-domain environment where each domain consists of computational, storage and communication resources grouped together for business or administrative reasons. Each domain is independently administrated and is free to deploy different technologies. Achieving better resource utilization calls for running load balancing techniques across different grid domains. This calls for novel load balancing techniques running in multi-domain scalable architecture to achieve better resource utilization without sacrificing domain security or privacy. The proposed multi-domain optical grid architecture assumes a dynamic on-demand reconfigurable optical network instead of pre-planned statically provisioned optical network. Dynamic reconfigurable optical grids presented in different projects such as Phosphorus (1) and G-lambda Projects (2). These projects present the structure and different components of optical network deployment in grids, and how these components interact to provide the grid applications with the services and capabilities making it able to manage its grid and optical network resource. In this paper, we present load balancing techniques in multi-domain hierarchical optical grid architecture that maintains the privacy, integration and scalability requirements. The privacy of a grid domain must be maintained in for confidentiality and commercial competition. For example, internal topology information of a domain should not be revealed to other domains (3). The domain privacy could be maintained by keeping the full resource information internally, while

Non-blocking minimum processes coordinated checkpointing for hierarchical computational grid

Non-blocking minimum processes coordinated checkpointing for hierarchical computational grid

Hybrid modelling and simulation of huge crowd over a hierarchical Grid architecture

The last decade has witnessed an explosion of the interest in technologies of large simulation with the rapid growth of both the complexity and the scale of problem domains. Modelling & simulation of crowd is a typical paradigm, especially when dealing with large crowd. On top of a hierarchical Grid simulation infrastructure, a simulation of evacuating tens of thousands of pedestrians in an urban area has been constructed. The simulation infrastructure can facilitate a large crowd simulation comprising models of different grains and various types in nature. A number of agent-based and computational models residing at two distinctive administrative domains operate together, which successfully presents the dynamics of the complex scenario at scales of both individual and crowd levels. Experimental results indicate that the proposed hybrid modelling & simulation approach can effectively cope with the size and complexity of a scenario involving a huge crowd.

Adaptive parallel job scheduling with resource admissible allocation on two-level hierarchical grids

We evaluate job scheduling algorithms that integrate both tasks of Grid scheduling: job allocation to Grid sites and local scheduling at the sites. We propose and analyze an adaptive job allocation scheme named admissible allocation. The main idea of this scheme is to set job allocation constraints, and dynamically adapt them to cope with different workloads and Grid properties. We present 3-approximation and 5-competitive algorithms named MLBa+PS and MCTa+PS for the case that all jobs fit to the smallest machine, while we derive an approximation factor of 9 and a competitive factor of 11 for the general case. To show practical applicability of our methods, we perform a comprehensive study of the practical performance of the proposed strategies and their derivatives using simulation. To this end, we use real workload traces and corresponding Grid configurations. We analyze nine scheduling strategies that require a different amount of information on three Grid scenarios. We demonstrate that our strategies perform well across ten metrics that reflect both user- and system-specific goals.

Experimental analysis of a Fast Adaptive Composite‐based grid expansion scheme for open boundary problems

SUMMARYPoisson's equation on unbounded domains was solved with a hierarchical grid coarsening approach on the basis of Stephen F. McCormick's Fast Adaptive Composite grid method. We were especially interested in the efficient interface treatment that is enabled by regular stencils. The error behavior of a second‐order scheme was empirically analyzed for an exemplary setup from molecular dynamics. Comparisons with previous methods were also performed and showed that our approach is competitive. Copyright © 2012 John Wiley & Sons, Ltd.

Parallel Distributed Trajectory Pattern Mining Based on Quadtree Search with Hierarchical Grid

In trajectory data mining which discovers frequent movement patterns from the trajectories of moving objects, both mining complex patterns and processing massive trajectory data are challenging problems. In this paper, we propose a new approach to trajectory data mining focusing on these problems. In order to make trajectories easier to process, traditional approaches quantize trajectories by a grid with a constant resolution. However, the optimal resolution often varies across different areas. This makes it difficult to mine complex patterns. Furthermore, the necessary amount of computational resources increases as the resolution becomes higher. This causes another problem that processing a massive dataset is difficult. To solve these problems, we propose a parallelized approach based on quadtree search with hierarchical grids. We employ a hierarchical grid structure with multiple resolutions to quantize trajectories. This approach initially searches for frequent patterns in a coarse grid level and drills down into a finer grid level to find more fine-grained patterns when needed. In this approach, we extract frequent movements as a pattern in terms of time duration of movements within a margin of error. Since an optimal time error varies across grid's resolutions, we propose a method for estimating optimal time errors. We also show a parallelization method based on MapReduce. In drilling down patterns, we mine child patterns in each region the parent pattern passes through and integrate child patterns along their parent pattern. In evaluation, experiments on real-word data show the effectiveness of our approach in mining complex patterns in low computational resources.

四分木構造格子を導入した自然河川における分岐点と合流点の数値解法

Numerical computation of river flows have been employed the general coordinate system to adjust a river plane form. An adjustment flexibility of the coordinate system is better but it is difficult to generate a grid system in order to compute stably because grid system is not determined uniquely. This study develops a new boundary fitting method introducing the hierarchical quad-tree grid system for computation of confluence and bifurcation in natural rivers. The numerical model with the quad-tree grid system apply to compute flow pattern in experiment flume and in natural river with bifurcation and confluence , the computed results agree with measured result of the flume and natural river well.

Allocating replicas in large-scale data grids using a QoS-aware distributed technique with workload constraints

An important technique to speed access in data grids is replication, which provides nearby replicas. In a data grid environment, resource availability, network latency and user request patterns may change. In this paper, we introduce a new distributed replica placement algorithm for hierarchical data grids that determines the positions of a minimum number of replicas expected to satisfy certain quality requirements. Our placement algorithm computes replica locations by minimising overall replication cost (read and update) while maximising Quality of Service (QoS) satisfaction for a given traffic pattern. Our algorithm also assumes that the workload capacity of each replica server is bounded. The problem is formulated using dynamic programming. We assess our algorithm using OptorSim. A comparison of our algorithm to its QoS-unconstrained counterpart and to two other existing algorithms (Greedy Add and Greedy Remove) shows that our algorithm can shorten job execution time significantly while requiring only moderate network bandwidth.

GENOCOP algorithm and hierarchical grid transformation for image warping of two dimensional gel eletrophoretic maps

Hierarchical grid transformation is a powerful approach to SDS 2DPAGE maps warping. The hierarchy of the warping transformation is able to model both global and local deformations of the gels and the algorithm can be stopped when a certain degree of accuracy in the image alignment is obtained. The numerical optimization of the position of the nodes of the grid that are responsible for the image warping is a multivariate task that can be solved efficiently using Genetic Algorithms. The use of Genetic Algorithms ensures that an optimal position of the nodes can be defined with a low computational cost with respect to other methods. The optimal positions of the nodes of the grid can be successfully used for defining a good warping of the gels.

An Approach to Construct Algebraic Two-Grid Preconditioners on Hierarchical Triangular Grids

In present paper an approach to construct algebraic two-grid preconditioners for symmetric positive definite matrices which arise in finite element approximation of elliptic equations. As a model problem, Poisson equation in equilateral unit triangle is considered. Multilevel subdivision of hierarchical triangular grids into substructures form the basis of multigrid technique. On each refinement level, the condition number of preconditioned stiffness matrix is evaluated.

Management and Placement of Replicas in a Hierarchical Data Grid

In large systems, data management is only possible through the use of replication techniques. In order to improve availability and ensure fast and efficient access, we propose in this paper a dynamic replication algorithm which takes into account also the placement of data in a hierarchical data grid. Experimental results show the effectiveness of our approach in terms of response time and availability of data in the system.