In this study, we developed a high speed eigenvalue solver that is the necessity of plasma stability analysis system for International Thermo-nuclear Experimental Reactor (ITER) on Cell cluster system. Our stability analysis system is developed in order to prevent damages to the ITER from plasma disruption. MARG2D, which is the main part of the system, analyzes the state of plasma with the measured conditions instantaneously. According to our estimation, the most time consuming part of MARG2D is eigensolver and we must solve resulted eigensystem whose dimension is hundred thousand within a second. However, current massively parallel processor (MPP) type supercomputer is not applicable for such instantaneous calculation, because the overhead of network communication becomes dominant. Therefore, we employ Cell cluster system, whose processor has higher performance than MPP’s, because we can obtain sufficient processing power with small number of processors. Furthermore, we developed novel eigenvalue solver with the consideration of hierarchical architecture of Cell cluster: Inter processor, intra processor, and SIMD parallelism. Finally, we succeeded to solve the block tridiagonal Hermitian matrix, which had 1024 diagonal blocks and the size of each block was 128 x 128 within a second.

The understanding of H diffusion in materials is pivotal to designing suitable processes. Though a nudged elastic band (NEB)+molecular dynamics (MD)/quantum mechanics (QM) algorithm has been developed to simulate H diffusion in materials by our group, it is often not computationally feasible for large-scale models on a conventional single system. We thus gridify the NEB+MD/QM algorithm on the top of an integrated framework developed by our group. A two days simulation on H diffusion in alumina has been successfully carried out over a trans-pacific grid infrastructure consisting of supercomputers provided by TeraGrid and AIST. In this paper, we describe the NEB+MD/QM algorithm, briefly introduce the framework middleware, present the grid enablement work, and report the techniques to achieve fault-tolerance and load-balance for sustainable simulation. We believe our experience is of benefit to both middleware developers and application users.

To ensure large-scale and long-time (LSLT) applications to run smoothly in a dynamic and heterogeneous grid environment, we have designed and implemented a WSRF-based framework with which users can reserve resources and request on-demand computing resources. The framework can be architecturely divided into three tiers: the tier providing client-side reservation and allocation APIs, the tier for reservation brokerage and resource allocation, and the tier for backend services. The reservation API is implemented for making and releasing a reservation, as well as for showing available reservations. The allocation API is implemented to request, to check, and to release a resource in a convenient way. The middle tier is designed to hide the complexity of the underlying grid infrastructure, and implemented to provide several allocation algorithms. One of the main backend services is Maui-based reservation service at present. A portal to facilitate the resource management is also available. In this paper, we present the API specification, the architecture, and the implementation of this framework. We also show a detailed experimental example.

Recent advances in grid infrastructure and middleware development have enabled various types of applications in science and engineering to be deployed on the grid. The characteristics of these applications and the diverse infrastructure and middleware solutions developed, utilized or adapted by PRAGMA member institutes are summarized. The applications include those for climate modeling, computational chemistry, bioinformatics and computational genomics, remote control of instruments, and distributed databases. Many of the applications are deployed to the PRAGMA grid testbed in routine basis experiments. Strategies for deploying applications without modifications, and those taking advantage of new programming models on the grid are explored and valuable lessons learned are reported. Comprehensive end to end solutions from PRAGMA member institutes that provide important grid middleware components and generalized models of integrating applications and instruments on the grid are also described.

We propose a reservation-based sustainable adaptive Grid supercomputing paradigm to enable tightly coupled computations of considerable scale (involving over 1,000 processors) and duration (over tens of continuous days) on a Grid of geographically distributed parallel supercomputers. The paradigm is demonstrated for an adaptive multiscale simulation application, in which accurate but compute-intensive quantum mechanical (QM) simulations are embedded within a classical molecular dynamics (Md) simulation only when and where high fidelity is required. Key technical innovations include: 1) an embedded divide-and-conquer algorithmic framework to maximally expose data and computation localities for enhanced scalability; 2) a buffered-cluster hybridization scheme to adaptively adjust MD/QM boundaries to maintain the model accuracy; and 3) a hybrid Grid remote procedure call (GridRPC) + message passing interface (MPI) Grid application framework to combine flexibility (adaptive resource allocation and migration), fault tolerance (automated fault recovery), and efficiency (scalable management of large computing resources). We have achieved an automated execution of multiscale MD/QM simulation on a Grid consisting of 6 supercomputer centers in Japan and the US (in total of 150 thousand processor-hours) for the dynamic simulation of implanted oxygen atoms in a silicon substrate, in which the number of processors changes dynamically on demand and resources are allocated and migrated dynamically according to both reservations and unexpected faults. The simulation results reveal a strong dependence of the oxygen penetration depth on the incident oxygen-beam position, which is useful information to further advance SIMOX (separation by implanted oxygen) technique to fabricate high speed and low power-consumption semiconductor devices.

Article Free Access Share on Local area metacomputing for multidisciplinary problems: a case study for fluid/structure coupled simulation Authors: Toshiya Kimura Center for Promotion of Computational Science and Engineering, Japan Atomic Energy Research Institute, 2-2-54, Nakameguro, Meguro-ku, Tokyo, 153-0061, Japan Center for Promotion of Computational Science and Engineering, Japan Atomic Energy Research Institute, 2-2-54, Nakameguro, Meguro-ku, Tokyo, 153-0061, JapanView Profile , Hiroshi Takemiya Center for Promotion of Computational Science and Engineering, Japan Atomic Energy Research Institute, 2-2-54, Nakameguro, Meguro-ku, Tokyo, 153-0061, Japan Center for Promotion of Computational Science and Engineering, Japan Atomic Energy Research Institute, 2-2-54, Nakameguro, Meguro-ku, Tokyo, 153-0061, JapanView Profile Authors Info & Claims ICS '98: Proceedings of the 12th international conference on SupercomputingJuly 1998 Pages 149–156https://doi.org/10.1145/277830.277861Online:13 July 1998Publication History 16citation357DownloadsMetricsTotal Citations16Total Downloads357Last 12 Months5Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF