On the Super-computational Background of the Research Centre Jülich

KFA Jülich is one of the largest big-science research centres in Europe; its scientific and engineering activities are ranging from fundamental research to applied science and technology. KFA's Central Institute for Applied Mathematics (ZAM) is running the large-scale computing facilities and network systems at KFA and is providing communication services, general-purpose and supercomputer capacity also for the HLRZ ("Höchstleistungsrechenzentrum") established in 1987 in order to further enhance and promote computational science in Germany. Thus, at KFA - and in particular enforced by ZAM - supercomputing has received high priority since more than ten years. What particle accelerators mean to experimental physics, supercomputers mean to Computational Science and Engineering: Supercomputers are the accelerators of theory

Direct-pNFS: Scalable, transparent, and versatile access to parallel file systems

Grid computations require global access to massive data stores. To meet this need, the GridNFS project aims to provide scalable, high-performance, transparent, and secure wide-area data management as well as a scalable and agile name space. While parallel file systems give high I/O throughput, they are highly specialized, have limited operating system and hardware platform support, and often lack strong security mechanisms. Remote data access tools such as NFS and GridFTP overcome some of these limitations, but fail to provide universal, transparent, and scalable remote data access. As part of GridNFS, this paper introduces Direct-pNFS, which builds on the NFSv4.1 protocol to meet a key challenge in accessing remote parallel file systems: high-performance and scalable data access without sacrificing transparency, security, orportability. Experiments with Direct-pNFS demonstrate I/O throughput that equals or out performs the exported parallel file system across a range of workloads.http://deepblue.lib.umich.edu/bitstream/2027.42/107917/1/citi-tr-07-2.pd

An Embedded System for applying High Performance Computing in Educational Learning Activity

HPC (High Performance Computing) has become more popular in the last few years. With the benefits on high computational power, HPC has impact on industry, scientific research and educational activities. Implementing HPC as a curriculum in universities could be consuming a lot of resources because well-known HPC system are using Personal Computer or Server. By using PC as the practical moduls it is need great resources and spaces.  This paper presents an innovative high performance computing cluster system to support education learning activities in HPC course with small size, low cost, and yet powerful enough. In recent years, High Performance computing usually implanted in cluster computing and require high specification computer and expensive cost. It is not efficient applying High Performance Computing in Educational research activiry such as learning in Class. Therefore, our proposed system is created with inexpensive component by using Embedded System to make High Performance Computing applicable for leaning in the class. Students involved in the construction of embedded system, built clusters from basic embedded and network components, do benchmark performance, and implement simple parallel case using the cluster.  In this research we performed evaluation of embedded systems comparing with i5 PC, the results of our embedded system performance of NAS benchmark are similar with i5 PCs. We also conducted surveys about student learning satisfaction that with embedded system students are able to learn about HPC from building the system until making an application that use HPC system

Development of an EVA systems cost model. Volume 1: Design guides synopsis-EVA equipment

EVA equipment design guides and crewman interfaces are provided. A summary presents data on suited crewman mobility capabilities and on off-the-shelf Skylab hardware for economy planning

A Server Consolidation Solution

Advances in server architecture has enabled corporations the ability to strategically redesign their data centers in order to realign the system infrastructure to business needs. The architectural design of physically and logically consolidating servers into fewer and smaller hardware platforms can reduce data center overhead costs, while adding quality of service. In order for the organization to take advantage of the architectural opportunity a server consolidation project was proposed that utilized blade technology coupled with the virtualization of servers. Physical consolidation reduced the data center facility requirements, while server virtualization reduced the number of required hardware platforms. With the constant threat of outsourcing, coupled with the explosive growth of the organization, the IT managers were challenged to provide increased system services and functionality to a larger user community, while maintaining the same head count. A means of reducing overhead costs associated with the in-house data center was to reduce the required facility and hardware resources. The reduction in the data center footprint required less real estate, electricity, fire suppression infrastructure, and HVAC utilities. In addition, since the numerous stand alone servers were consolidated onto a standard platform system administration became more agile to business opportunities.

Enhancing functionality and performance in the PVM network computing system

The research funded by this grant is part of an ongoing research project in heterogeneous distributed computing with the PVM system, at Emory as well as at Oak Ridge Labs and the University of Tennessee. This grant primarily supports research at Emory that continues to evolve new concepts and systems in distributed computing, but it also includes the PI`s ongoing interaction with the other groups in terms of collaborative research as well as software systems development and maintenance. We have continued our second year efforts (July 1995 - June 1996), on the same topics as during the first year, namely (a) visualization of PVM programs to complement XPVM displays; (b) I/O and generalized distributed computing in PVM; and (c) evolution of a multithreaded concurrent computing model. 12 refs

HEC: Collaborative Research: SAM^2 Toolkit: Scalable and Adaptive Metadata Management for High-End Computing

The increasing demand for Exa-byte-scale storage capacity by high end computing applications requires a higher level of scalability and dependability than that provided by current file and storage systems. The proposal deals with file systems research for metadata management of scalable cluster-based parallel and distributed file storage systems in the HEC environment. It aims to develop a scalable and adaptive metadata management (SAM2) toolkit to extend features of and fully leverage the peak performance promised by state-of-the-art cluster-based parallel and distributed file storage systems used by the high performance computing community. There is a large body of research on data movement and management scaling, however, the need to scale up the attributes of cluster-based file systems and I/O, that is, metadata, has been underestimated. An understanding of the characteristics of metadata traffic, and an application of proper load-balancing, caching, prefetching and grouping mechanisms to perform metadata management correspondingly, will lead to a high scalability. It is anticipated that by appropriately plugging the scalable and adaptive metadata management components into the state-of-the-art cluster-based parallel and distributed file storage systems one could potentially increase the performance of applications and file systems, and help translate the promise and potential of high peak performance of such systems to real application performance improvements. The project involves the following components: 1. Develop multi-variable forecasting models to analyze and predict file metadata access patterns. 2. Develop scalable and adaptive file name mapping schemes using the duplicative Bloom filter array technique to enforce load balance and increase scalability 3. Develop decentralized, locality-aware metadata grouping schemes to facilitate the bulk metadata operations such as prefetching. 4. Develop an adaptive cache coherence protocol using a distributed shared object model for client-side and server-side metadata caching. 5. Prototype the SAM2 components into the state-of-the-art parallel virtual file system PVFS2 and a distributed storage data caching system, set up an experimental framework for a DOE CMS Tier 2 site at University of Nebraska-Lincoln and conduct benchmark, evaluation and validation studies

Active yellow pages: a pipelined resource management architecture for wide-area network computing

This paper describes a novel, pipelined resource management architecture for computational grids. The design is based on two key realizations. One is that resource management involves a sequence of tasks that is best handled by a pipeline. As shown in the paper, this approach results, in a scalable architecture for decentralized scheduling. The other realization is that static aggregation of resources for improved scheduling is inadequate in wide-area computing environments because the needs of users and jobs change with both, location and time. The described architecture addresses this problem by dynamically aggregating resources in a manner that continuously optimizes system response. This is accomplished by way of an active yellow pages directory that allows aggregation constraints to be (re)defined on the fly. An initial prototype of the active yellow pages service has been deployed in the PUNCH network computing environment. Experiences with the production PUNCH system and preliminary results from controlled experiments indicate that the active yellow pages service performs well.Peer Reviewe