981 research outputs found
A Massive Data Parallel Computational Framework for Petascale/Exascale Hybrid Computer Systems
Heterogeneous systems are becoming more common on High Performance Computing
(HPC) systems. Even using tools like CUDA and OpenCL it is a non-trivial task
to obtain optimal performance on the GPU. Approaches to simplifying this task
include Merge (a library based framework for heterogeneous multi-core systems),
Zippy (a framework for parallel execution of codes on multiple GPUs), BSGP (a
new programming language for general purpose computation on the GPU) and
CUDA-lite (an enhancement to CUDA that transforms code based on annotations).
In addition, efforts are underway to improve compiler tools for automatic
parallelization and optimization of affine loop nests for GPUs and for
automatic translation of OpenMP parallelized codes to CUDA.
In this paper we present an alternative approach: a new computational
framework for the development of massively data parallel scientific codes
applications suitable for use on such petascale/exascale hybrid systems built
upon the highly scalable Cactus framework. As the first non-trivial
demonstration of its usefulness, we successfully developed a new 3D CFD code
that achieves improved performance.Comment: Parallel Computing 2011 (ParCo2011), 30 August -- 2 September 2011,
Ghent, Belgiu
3rd EGEE User Forum
We have organized this book in a sequence of chapters, each chapter associated with an application or technical theme introduced by an overview of the contents, and a summary of the main conclusions coming from the Forum for the chapter topic. The first chapter gathers all the plenary session keynote addresses, and following this there is a sequence of chapters covering the application flavoured sessions. These are followed by chapters with the flavour of Computer Science and Grid Technology. The final chapter covers the important number of practical demonstrations and posters exhibited at the Forum. Much of the work presented has a direct link to specific areas of Science, and so we have created a Science Index, presented below. In addition, at the end of this book, we provide a complete list of the institutes and countries involved in the User Forum
Quantum ESPRESSO: a modular and open-source software project for quantum simulations of materials
Quantum ESPRESSO is an integrated suite of computer codes for
electronic-structure calculations and materials modeling, based on
density-functional theory, plane waves, and pseudopotentials (norm-conserving,
ultrasoft, and projector-augmented wave). Quantum ESPRESSO stands for "opEn
Source Package for Research in Electronic Structure, Simulation, and
Optimization". It is freely available to researchers around the world under the
terms of the GNU General Public License. Quantum ESPRESSO builds upon
newly-restructured electronic-structure codes that have been developed and
tested by some of the original authors of novel electronic-structure algorithms
and applied in the last twenty years by some of the leading materials modeling
groups worldwide. Innovation and efficiency are still its main focus, with
special attention paid to massively-parallel architectures, and a great effort
being devoted to user friendliness. Quantum ESPRESSO is evolving towards a
distribution of independent and inter-operable codes in the spirit of an
open-source project, where researchers active in the field of
electronic-structure calculations are encouraged to participate in the project
by contributing their own codes or by implementing their own ideas into
existing codes.Comment: 36 pages, 5 figures, resubmitted to J.Phys.: Condens. Matte
Global Grids and Software Toolkits: A Study of Four Grid Middleware Technologies
Grid is an infrastructure that involves the integrated and collaborative use
of computers, networks, databases and scientific instruments owned and managed
by multiple organizations. Grid applications often involve large amounts of
data and/or computing resources that require secure resource sharing across
organizational boundaries. This makes Grid application management and
deployment a complex undertaking. Grid middlewares provide users with seamless
computing ability and uniform access to resources in the heterogeneous Grid
environment. Several software toolkits and systems have been developed, most of
which are results of academic research projects, all over the world. This
chapter will focus on four of these middlewares--UNICORE, Globus, Legion and
Gridbus. It also presents our implementation of a resource broker for UNICORE
as this functionality was not supported in it. A comparison of these systems on
the basis of the architecture, implementation model and several other features
is included.Comment: 19 pages, 10 figure
A Taxonomy of Workflow Management Systems for Grid Computing
With the advent of Grid and application technologies, scientists and
engineers are building more and more complex applications to manage and process
large data sets, and execute scientific experiments on distributed resources.
Such application scenarios require means for composing and executing complex
workflows. Therefore, many efforts have been made towards the development of
workflow management systems for Grid computing. In this paper, we propose a
taxonomy that characterizes and classifies various approaches for building and
executing workflows on Grids. We also survey several representative Grid
workflow systems developed by various projects world-wide to demonstrate the
comprehensiveness of the taxonomy. The taxonomy not only highlights the design
and engineering similarities and differences of state-of-the-art in Grid
workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure
Many-Task Computing and Blue Waters
This report discusses many-task computing (MTC) generically and in the
context of the proposed Blue Waters systems, which is planned to be the largest
NSF-funded supercomputer when it begins production use in 2012. The aim of this
report is to inform the BW project about MTC, including understanding aspects
of MTC applications that can be used to characterize the domain and
understanding the implications of these aspects to middleware and policies.
Many MTC applications do not neatly fit the stereotypes of high-performance
computing (HPC) or high-throughput computing (HTC) applications. Like HTC
applications, by definition MTC applications are structured as graphs of
discrete tasks, with explicit input and output dependencies forming the graph
edges. However, MTC applications have significant features that distinguish
them from typical HTC applications. In particular, different engineering
constraints for hardware and software must be met in order to support these
applications. HTC applications have traditionally run on platforms such as
grids and clusters, through either workflow systems or parallel programming
systems. MTC applications, in contrast, will often demand a short time to
solution, may be communication intensive or data intensive, and may comprise
very short tasks. Therefore, hardware and software for MTC must be engineered
to support the additional communication and I/O and must minimize task dispatch
overheads. The hardware of large-scale HPC systems, with its high degree of
parallelism and support for intensive communication, is well suited for MTC
applications. However, HPC systems often lack a dynamic resource-provisioning
feature, are not ideal for task communication via the file system, and have an
I/O system that is not optimized for MTC-style applications. Hence, additional
software support is likely to be required to gain full benefit from the HPC
hardware
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