http://dsa-research.org/lib/exe/fetch.php?id=publications%3Agrid%3Autility&cache=cache&media=publications:grid:fgcs09_lhl.pdf

A decentralized model for scheduling independent tasks in Federated Grids

The application hosting environment: Lightweight middleware for grid-based computational science

High-resolution unsteady three-dimensional flow simulations in large intracranial arterial networks of a healthy subject and a patient with hydrocephalus have been performed. The large size of the computational domains requires the use of thousands of computer processors and solution of the flow equations with approximately one billion degrees of freedom. We have developed and implemented a two-level domain decomposition method, and a new type of outflow boundary condition to control flow rates at tens of terminal vessels of the arterial network. In this paper, we demonstrate the flow patterns in the normal and abnormal intracranial arterial networks using patient-specific data.

/pdf/simulation-of-the-human-intracranial-arterial-tree-4jsqalgpr3.pdf

Simulation of the human intracranial arterial tree

Many emerging high performance applications require distributed infrastructure that is significantly more powerful and flexible than traditional grids. Such applications require the optimization, close integration, and control of all grid resources, including networks. The EnLIGHTened (ENL) computing project has designed an architectural framework that allows grid applications to dynamically request (in-advance or on-demand) any type of grid resource: computers, storage, instruments, and deterministic, high-bandwidth network paths, including lightpaths. Based on application requirements, the ENL middleware communicates with grid resource managers and, when availability is verified, co-allocates all the necessary resources. ENLpsilas domain network manager controls all network resource allocations to dynamically setup and delete dedicated circuits using generalized multiprotocol label switching (GMPLS) control plane signaling. In order to make optimal brokering decisions, the ENL middleware uses near-real-time performance information about grid resources. A prototype of this architectural framework on a national-scale testbed implementation has been used to demonstrate a small number of applications. Based on this, a set of changes for the middleware have been laid out and are being implemented.

EnLIGHTened Computing: An architecture for co-allocating network, compute, and other grid resources for high-end applications

It is generally accepted that the ability to develop large-scale distributed applications has lagged seriously behind other developments in cyberinfrastructure. In this paper, we provide insight into how such applications have been developed and an understanding of why developing applications for distributed infrastructure is hard. Our approach is unique in the sense that it is centered around half a dozen existing scientific applications; we posit that these scientific applications are representative of the characteristics, requirements, as well as the challenges of the bulk of current distributed applications on production cyberinfrastructure (such as the US TeraGrid). We provide a novel and comprehensive analysis of such distributed scientific applications. Specifically, we survey existing models and methods for large-scale distributed applications and identify commonalities, recurring structures, patterns and abstractions. We find that there are many ad hoc solutions employed to develop and execute distributed applications, which result in a lack of generality and the inability of distributed applications to be extensible and independent of infrastructure details. In our analysis, we introduce the notion of application vectors: a novel way of understanding the structure of distributed applications. Important contributions of this paper include identifying patterns that are derived from a wide range of real distributed applications, as well as an integrated approach to analyzing applications, programming systems and patterns, resulting in the ability to provide a critical assessment of the current practice of developing, deploying and executing distributed applications. Gaps and omissions in the state of the art are identified, and directions for future research are outlined.

/pdf/distributed-computing-practice-for-large-scale-science-and-3t440vxb6o.pdf

Distributed computing practice for large-scale science and engineering applications

In response to a joint call from US's NSF and UK's EPSRC for applications that aim to utilize the combined computational resources of the US and UK, three computational science groups from UCL, Tufts and Brown Universities teamed up with a middleware team from NIU/Argonne to meet the challenge. Although the groups had three distinct codes and aims, the projects had the underlying common feature that they were comprised of large-scale distributed applications which required high-end networking and advanced middleware in order to be effectively deployed. For example, cross-site runs were found to be a very effective strategy to overcome the limitations of a single resource. The seamless federation of a grid-of-grids remains difficult. Even if interoperability at the middleware and software stack levels were to exist, it would not guarantee that the federated grids can be utilized for large scale distributed applications. There are important additional requirements for example, compatible and consistent usage policy, automated advanced reservations and most important of all co-scheduling. This paper outlines the scientific motivation and describes why distributed resources are critical for all three projects. It documents the challenges encountered in using a grid-of-grids and some of the solutions devised in response.

NEKTAR, SPICE and Vortonics: using federated grids for large scale scientific applications

Grid solutions for biological and physical cross-site simulations on the TeraGrid

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Dong

Author Tools

Chat about Author

Papers

NEKTAR, SPICE and Vortonics: using federated grids for large scale scientific applications

Grid solutions for biological and physical cross-site simulations on the TeraGrid