The Kantorovich Metric in Computer Science: A Brief Survey

In contrast to its wealth of applications in mathematics, the Kantorovich metric started to be noticed in computer science only in recent years. We give a brief survey of its applications in probabilistic concurrency, image retrieval, data mining, and bioinformatics. This paper highlights the usefulness of the Kantorovich metric as a general mathematical tool for solving various kinds of problems in rather unrelated domains.     

Data Layout Transformation Exploiting Memory-Level Parallelism in Structured Grid Many-Core Applications

We present automatic data layout transformation as an effective compiler performance optimization for memory-bound structured grid applications. Structured grid applications include stencil codes and other code structures using a dense, regular grid as the primary data structure. Fluid dynamics and heat distribution, which both solve partial differential equations on a discretized representation of space, are representative of many important structured grid applications. Using the information available through variable-length array syntax, standardized in C99 and other modern languages, we enable automatic data layout transformations for structured grid codes with dynamically allocated arrays. We also present how a tool can guide these transformations to statically choose a good layout given a model of the memory system, using a modern GPU as an example. A transformed layout that distributes concurrent memory requests among parallel memory system components provides substantial speedup for structured grid applications by improving their achieved memory-level parallelism. Even with the overhead of more complex address calculations, we observe up to 10.94X speedup over the original layout, and a 1.16X performance gain in the worst case.     

A high performance grid-web service framework for the identification of ‘conserved sequence tags’

The continuous increasing of computing power in biological research places a threshold to the single host use and suggests an approach based on distributed computing. An emerging solution is grid technology, which allows organization to make better use of existing computing resources by providing them with a single, transparent, aggregated source of computing power. Equally, bioinformatics analysis often involves many web services, allowing shared access to information and helping the biologist to design, describe, record complex experiments. A new generation of grid infrastructure, where web services are building blocks, allow managent of a web services workflow.This work shows a tool for the identification and functional annotation of ‘Conserved Sequence Tags’ (CSTs) through cross-species genome comparisons, deployed on a Grid System Architecture, based on Web Services concepts and technologies.     

Visualizing Validation of Protein Surface Classifiers

Many bioinformatics applications construct classifiers that are validated in experiments that compare their results to known ground truth over a corpus. In this paper, we introduce an approach for exploring the results of such classifier validation experiments, focusing on classifiers for regions of molecular surfaces. We provide a tool that allows for examining classification performance patterns over a test corpus. The approach combines a summary view that provides information about an entire corpus of molecules with a detail view that visualizes classifier results directly on protein surfaces. Rather than displaying miniature 3D views of each molecule, the summary provides 2D glyphs of each protein surface arranged in a reorderable, small‐multiples grid. Each summary is specifically designed to support visual aggregation to allow the viewer to both get a sense of aggregate properties as well as the details that form them. The detail view provides a 3D visualization of each protein surface coupled with interaction techniques designed to support key tasks, including spatial aggregation and automated camera touring. A prototype implementation of our approach is demonstrated on protein surface classifier experiments.     

HECTOR: Enabling Microarray Experiments over the Hellenic Grid Infrastructure

Biologists, medical experts, biochemical engineers and researchers working on DNA microarray experiments are increasingly turning on Grid computing with the scope of leveraging the Grid’s computing power, immense storage resources, and quality of service to the expedient processing of a wide range of datasets. In this paper we present a combined experience of grid application experts and bioinformatics scientists in deploying a pilot service enabling computationally efficient processing and analysis of data stemming from microarray experiments. This pilot service is accessible over the Hellenic portion of the EGEE grid and has been demonstrated in the scope of several public events. We highlight the process of grid application enablement, grid deployment challenges, as well as lessons learnt from a bi-annual effort to port and deploy a MATLAB DNA microarray application on a production grid. In addition to describing the parallelization of the application, we also emphasize on the development of a distributed federated database for storing and post-processing the results of the microarray experiments. Overall we believe that our experience could be proven valuable not only to microarray data scientists but also to other Grid users that intend to Grid-enable and deploy their applications.     

The deployment and evaluation of a bioinformatics grid platform - The HUST_Bio_Grid

This paper reports our experience in the deployment of the Hust_Bio_Grid platform, which is a grid sub-platform that is specifically tailored towards the needs of bioinformatics. It enables the collaboration of multiple research institutes and facilitates the sharing of resources such as hardware, database software tools, etc. In particular, this paper presents a case study that addresses the deployment and reuse of services and applications through a standardized easy to use interface. It discusses the deployment of services including the requirements, the interface and the deployment process as a whole. Selected example services are discussed and relevant performance evaluations are presented. Through this scheme, all users including domain specific experts as well as generic software developers can contribute and deploy their own applications to the grid platform in a simple and efficient way. Thus, the actual functionality of the overall platform and the usability thereof is defined through the actual consumers and their specific needs.     

An agent-based approach to tool integration

Tool integration is a very difficult challenge. Problems may arise at different abstraction levels and from several sources such as heterogeneity of manipulated data, incompatible interfaces, or uncoordinated services, to name just a few examples. On the other hand, applications based on the coherent composition of activities, components, services, and data from heterogeneous sources are increasingly present in our everyday lives. Consequently, tool integration takes on increasing significance.In this paper we analyze the tool-integration problem at different abstraction levels and discuss different views on a layered software architecture that we have designed specifically for a middleware that supports the execution of distributed applications for the orchestration of human/system activities. We noticed that the agent paradigm provided a suitable technology for abstraction in tool integration. Throughout the paper, the discussion refers to a case study in the bioinformatics domain.     

网格研究及其开发环境*

探讨了网格研究的基础理论、核心问题、具体研究内容和难点;仿真是研究网格资源管理和调度问题的重要方法,分析和评价了目前主要仿真工具的特点及应用;GT3已经成为网格项目开发的主流工具,给出了建立GT3 Core网格服务开发平台的方法;介绍了基于CGSP(China Grid Support Platform)的网格开发环境.以期有助于网格的创新研究和应用开发.     

Bioinformatics experiences important breakthroughs

Several important recent breakthroughs help accelerate development of the emerging field of bioinformatics. For example, the US Department of Energy is creating a nationwide grid that will let geographically dispersed scientists share computing and data-storage resources for bioinformatics and other types of research involving complex calculations and large datasets     

基于性能监控的网格应用自适应调节机制

如何在动态网格环境中获取网格应用的更好性能是网格技术一直关注的课题．为实时地调整和改善应用性能，介绍了一种基于性能监控的网格应用自适应调节机制，该机制运用模糊控制技术，不依赖于应用对象的数学模型，对无法建模或很难建模的复杂对象，能利用人的经验知识完成调节任务．结合网格监控体系结构(GMA)，设计了一个实现该机制的模型，描述了模型中各模块的具体功能，给出了实现技术及相关算法，最后对这种自适应调节机制的性能进行了评估．该模型结构建立在GMA基础之上，具有很好的可扩展性和移植性．     

CFD网格应用平台研究

CFD网格应用平台是ChinaGrid5大应用平台之一,它为各种不同的CFD应用提供了网格基础设施。平台采用了两层架构：上层基于WSRF服务,下层基于并行计算。为了无缝整合各种CFD应用,平台定义了一组包括CFD工作流模板和CFD分类码的重要概念,使用了一系列如CGNS数据可视化工具GVisual的关键技术。目前基于Service Domain的平台原型系统已经开发完成,性能测试表明CFD应用移植其到平台上后性能获得提高。     

网格计算开发平台GBuilder的研究与实现

网格计算的快速开发问题是制约网格技术普遍使用的关键问题之一。为解决这个问题,自行设计和实现了用于网格计算应用快速开发的集成网格计算开发平台GBuilder。文中阐述了GBuilder的定位以及体系结构,并且对体系结构的各个组成组件的功能做了简单的说明,然后介绍了GBuilder中一些关键问题的实现方法,这些方法包括基于开放平台Eclipse的实现思路和网格计算开发的流程设计,最后给出了在GBuilder中采用适配器设计模式集成Globus工具箱的方法。     

基于GOS的国家网格集成环境及应用实例开发*

中国国家网格作为国内最主要的网格为用户提供了良好的计算服务.详细讨论了网格中间件系统软件GOS的功能和结构,以及基于GOS的中国国家网格集成环境,给出了生物信息软件MEME在国家网格环境下的集成实现,并提出了今后的工作方向.     

A survey of life sciences applications on the grid

The availability of powerful microprocessors and improvements in the performance of networks has enabled high performance computing on wide-area, distributed systems. Computational grids, by integrating diverse, geographically distributed and essentially heterogeneous resources provide the infrastructure for solving large-scale problems. However, heterogeneity, on the one hand allows for scalability, but on the other hand makes application development and deployment for such an environment extremely difficult. The field of life sciences has been an explosion in data over the past decade. The data acquired needs to be processed, interpreted and analyzed to be useful. The large resource needs of bioinformatics allied to the large number of data-parallel applications in this field and the availability of a powerful, high performance, computing grid environment lead naturally to opportunities for developing grid-enabled applications. This survey, done as part of the Life Sciences Research Group (a research group belonging to the Global Grid Forum) attempts to collate information regarding grid-enabled applications in this field. Arun Krishnan, Ph.D.: He did his undergraduate in Electrochemical Engineering in the Central Electrochemical Research Institute in India and went on to do his Ph.D. in Advanced Process Control from the University of South Carolina. He then worked in the control and high performance computing industries for about 3 years before moving to the Bioinformatics Institute in Singapore. He is currently a Young Investigator for the Distributed Computing in Biomedicine Group at BII. His research interests include parallel and distributed computing with special emphasis on grid computing and its application to the biomedical area. He is also interested in developing parallel algorithms for sequence analysis and protein structure prediction.     

Trustworthy remote compiling services for grid-based scientific applications

Grid computing, which is characterized by large-scale sharing and collaboration of dynamic resources, is becoming an emerging computing platform on a global scale for data-intensive and computation-intensive scientific application. However, the complications of large-scale scientific computations and simulations harnessing massive computing resources are compounded by extensive heterogeneity in environments arising from “the Grid.” Scientists and engineers lack an intuitive grid-based compilation tool, which has contributed to the difficulty of exploiting these diverse resources and developing their applications on the grid. While manual configuration of various toolkits simplifying the end-to-end completion of a job is adequate for a computational grid with a limited number of nodes, the compilation procedure becomes inefficient for a computational grid with an increasing number of heterogeneous computational service providers. On the other hand, a global-scale computational grid is a potentially untrustworthy computing environment. How to take advantage of the potentially untrustworthy grid resources to provide trustworthy computational services for large-scale scientific applications is another critical issue. In this article, a remote compiling service for a heterogeneous computational grid is developed. In addition to running compilation tasks, the remote compiling service provides security enforcement and validation facilities, including intermediate value checking, secure source program submission, restricted compilation, and binary inspection, to support trustworthy compilation and execution of grid-based scientific applications. Overall, it is expected that our remote compiling services on the grid can tackle the heterogeneity problem of the grid and provide a secure, trustworthy, reliable, and state-of-the-art mechanism to develop grid-aware scientific applications.

A distributed evolutionary approach for multisite mapping on grids

In this paper attention is concentrated on the mapping of computationally intensive multi‐task applications onto shared computational grids. This problem, already known to be as NP‐complete in parallel systems, becomes even more arduous in such environments. To find a near‐optimal mapping solution a parallel version of a Differential Evolution algorithm is presented and evaluated on different applications and operating conditions of the grid nodes. The purpose is to select for a given application the mapping solutions that minimize the greatest among the time intervals which each node dedicates to the execution of the tasks assigned to it. The experiments, effected with applications represented as task interaction graphs, demonstrate the ability of the evolutionary tool to perform multisite grid mapping, and show that the parallel approach is more effective than the sequential version both in enhancing the quality of the solution and in the time needed to get it. Copyright © 2011 John Wiley & Sons, Ltd.     

ParTransgrid: A scalable parallel preprocessing tool for unstructured-grid cell-centered computational fluid dynamics applications

The development of a basic scalable preprocessing tool is the key routine to accelerate the entire computational fluid dynamics (CFD) workflow toward the exascale computing era. In this work, a parallel preprocessing tool, called ParTransgrid, is developed to translate the general grid format like CFD General Notation System into an efficient distributed mesh data format for large-scale parallel computing. Through ParTransgrid, a flexible face-based parallel unstructured mesh data structure designed in Hierarchical Data Format can be obtained to support various cell-centered unstructured CFD solvers. The whole parallel preprocessing operations include parallel grid I/O, parallel mesh partition, and parallel mesh migration, which are linked together to resolve the run-time and memory consumption bottlenecks for increasingly large grid size problems. An inverted index search strategy combined with a multi-master-slave communication paradigm is proposed to improve the pairwise face matching efficiency and reduce the communication overhead when constructing the distributed sparse graph in the phase of parallel mesh partition. And we present a simplified owner update rule to fast the procedure of raw partition boundaries migration and the building of shared faces/nodes communication mapping list between new sub-meshes with an order of magnitude of speed-up. Experiment results reveal that ParTransgrid can be easily scaled to billion-level grid CFD applications, the preparation time for parallel computing with hundreds of thousands of cores is reduced to a few minutes.     

教育资源网格模型及副本创建策略

教育资源网格是解决目前分布式教育资源共享问题的有效手段.针对中小学教育资源共享问题,提出了层次式的教育资源网格模型,定义了各层节点的功能.通过与欧洲数据网格对比,分析了教育资源网格的特点.基于层次式的教育资源网格,对影响副本创建策略性能的因素进行了分析,然后引入网络带宽和文件大小两个参数,提出了一种动态副本创建策略(dynamic replica creation strategy,简称EDRS).利用数据网格模拟工具OptorSim构建了教育资源网格虚拟环境,分析比较了EDRS策略与Caching-LRU策略、Caching-LFU策略和基于经济模型的副本创建策略的性能.最后,综合各项指标分析了不同策略对教育资源网格系统性能的影响.结果表明,EDRS策略在教育资源网格应用中有着更好的系统性能.     

GSML网格编程语言的一种实现方法

随着网格计算技术的不断发展，部署网格应用的环境越来越多，而网格编程语言还停留在C，Java这样的程序设计语言上，GSML是在中科院计算所织女星网格项目中设计的高级编程语言和用户界面语言，它采用了一种标记语言实现编程技术，旨在降低网格编程的难度，提高开发和部署网格应用的效率，介绍了对该语言的一种实现方法，讨论了GSML实现过程中需要解决的关键技术问题，以及网格社区等涉及GSML实现的相关内容。     

A software “tool kit” in C for the application of spherical geodesic grids in paleoclimatology

A popular technique in paleoclimatology is the definition of occurrences of climate-sensitive lithofacies, such as evaporite deposits, using a global grid system. The simplest and most widely used grid systems in paleoclimatology are orthogonal grids that use lines of latitude and longitude as grid-cell boundaries. Occurrences defined using orthogonal grids, however, can differ greatly in size and shape because lines of longitude converge at the poles, distorting the shape of the grid system. As a result of this distortion, the latitude at which the occurrences were defined can affect the number and distribution of occurrences. As an alternative, spherical geodesic systems can be used. Spherical geodesic systems have near-equal area and near-equal shape grid-cells for the entire sphere, which significantly reduce biases introduced by the grid system. Spherical geodesic systems can make paleoclimatic studies using occurrences of climate-sensitive lithofacies more reliable. To make spherical geodesic systems practical for paleoclimate applications, a “tool kit” of programs written in C has been assembled. Four programs are included in the tool kit: DESIGNER, which designs spherical geodesic grids, PLOTTER, which generates import files for Terra Mobilis™ and PGIS/Mac™ to display the grids, MAPPER, which defines occurrences using the grids, and ROTATOR, which rotates data about Euler poles. Middle Devonian evaporite data for North America were compiled to demonstrate each of the functions.