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IEEE Symposium on Mass Storage systems

作者： K.W. Preslan A.P. Barry J.E. Brassow G.M. Erickson E. Nygaard C.J. Sabol S.R. Soltis D.C. Teigland M.T. O'Keefe Parallel Computer Systems Laboratory Department of Electrical and Computer Engineering University of Minnesota USA

In computer systems today, speed and responsiveness is often determined by network and storage subsystem performance. Faster, more scalable networking interfaces like Fibre Channel and Gigabit Ethernet provide the scaffolding from which higher performance implementations may be constructed, but new thinking is required about how machines interact with network-enabled storage devices. We have developed a Linux file system called GFS (the Global File System) that allows multiple Linux machines to access and share disk and tape devices on a Fibre Channel or SCSI storage network. We plan to extend GFS by transporting packetized SCSI commands over IP so that any GFS-enabled Linux machine can access shared network devices. GFS will perform well as a local file system, as a traditional network file system running over LP, and as a high-performance cluster file system running over storage networks like Fibre Channel. GFS device sharing provides a key cluster-enabling technology for Linux, helping to bring the availability, scalability, and load balancing benefits of clustering to Linux. Our goal is to develop a scalable, (in number of clients and devices, capacity, connectivity, and bandwidth) server-less file system that integrates IF-based network attached storage (NAS) and Fibre-Channel-based storage area networks (SAN). We call this new architecture Storage Area InterNetworking (SAINT). It exploits the speed and device scalability of SAN clusters, and provides the client scalability and network interoperability of NAS appliances. Our Linux port shows that the GFS architecture is portable across different platforms, and we are currently working on a port to NetBSD. The GFS code is open source (GPL) software freely available on the Internet at http://***.

关键词： File systems Linux Optical fiber devices Scalability Storage area networks computer networks Delay Ethernet networks Availability Load management

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Data management for large-scale scientific computations in high performance distributed systems

Data management for large-scale scientific computations in h...

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International Symposium on High Performance distributed Computing

作者： A. Choudhary M. Kandemir H. Nagesh J. No X. Shen V. Taylor S. More R. Thakur Center for Parallel and Distributed Computing Department of Electrical and Computer Engineering Northwestern University Evanston IL USA Mathematics and Computer Science Division Argonne National Laboratory Argonne IL USA

With the increasing number of scientific applications manipulating huge amounts of data, effective data management is an increasingly important problem. Unfortunately, so far the solutions to this data management problem either require deep understanding of specific storage architectures and file layouts (as in high-performance file systems) or produce unsatisfactory I/O performance in exchange for ease-of-use and portability (as in relational DBMSs). In this paper we present a new environment which is built around an active meta-data management system (MDMS). The key components of our three-tiered architecture are user application, the MDMS, and a hierarchical storage system (HSS). Our environment overcomes the performance problems of pure database-oriented solutions, while maintaining their advantages in terms of ease-of-use and portability. The high levels of performance are achieved by the MDMS, with the aid of user-specified directives. Our environment supports a simple, easy-to-use yet powerful user interface, leaving the task of choosing appropriate I/O techniques to the MDMS. We discuss the importance of an active MDMS and show how the three components, namely application, the MDMS, and the HSS, fit together. We also report performance numbers from our initial implementation and illustrate that significant improvements are made possible without undue programming effort.

关键词： Large-scale systems distributed computing High performance computing Data visualization engineering management Concurrent computing Relational databases Art Data analysis Image analysis

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Superconducting processors for HTMT: issues and challenges

Superconducting processors for HTMT: issues and challenges

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Frontiers of Massively parallel Computation

作者： K.B. Theobald G.R. Gao T.L. Sterling Computer Architecture and Parallel Systems Laboratory Department of Electrical and Computer Engineering University of Delaware Newark DE USA NASA Jet Propulsion Laboratory /Center for Advanced Computing Research California Institute of Technology Pasadena CA USA

The Hybrid Technology Multi-Threading project is a long-term study of the feasibility of combining several emerging technologies to reach 1 petaFLOPS within ten years. HTMT will combine high-speed superconductor processors, semiconductor memories with built-in processors, high-speed optical interconnects, and high-density holographic storage. While there are major challenges in all aspects of this project, those in processor architecture are the focus of this paper. Fundamental differences between RSFQ circuits and conventional semiconductor circuits, including a radical jump in clock speed, make today's processor design approaches inappropriate for HTMT. Sequential instruction dispatching, even within the lowest programming unit (a strand), will lead to unacceptably high latencies, hence poor performance. We propose alternative processor designs which use fine-grain synchronizations between individual instructions in order to avoid these bottlenecks.

关键词： Random access memory Optical buffering Holography Holographic optical components Delay computer architecture Optical interconnections electrical capacitance tomography Quantum computing Clocks

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A non-blocking recovery algorithm for causal message logging

A non-blocking recovery algorithm for causal message logging

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Reliable distributed systems

作者： J.R. Mitchell V.K. Garg Parallel and Distributed Systems Laboratory Department of Electrical and Computer Engineering University of Texas Austin

In the recovery of failed processes in a distributed program, causal logging schemes offer several benefits. These benefits include no rollback of unfailed processes and simple approaches to output commit. Unfortunately, previous approaches to the recovery of multiple simultaneous failures require that the distributed execution be blocked or that recovering processes coordinate. The latter requires assumptions which are not satisfactory. In this paper we present a solution that has neither of these drawbacks.

关键词： History Laboratories Optimization methods computer crashes

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Strings: a high-performance distributed shared memory for symmetrical multiprocessor clusters 98

Strings: a high-performance distributed shared memory for sy...

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International Symposium on High Performance distributed Computing

作者： S. Roy V. Chaudhary Parallel and Distributed Computing Laboratory Department of Electrical and Computer Engineering Wayne State University Detroit MI USA

ISBN: (纸本)9780818685798

Introduces Strings, a high-performance distributed shared memory system designed for clusters of symmetrical multiprocessors (SMPs). The distinguishing feature of this system is the use of a fully multithreaded runtime system, written using POSIX threads. Strings also allows multiple application threads to be run on each node in a cluster. Since most modern UNIX systems can multiplex these threads on kernel-level lightweight processes, applications written using Strings can use all the processors in a SMP machine. This paper describes some of the architectural details of the system and analyzes the performance improvements with two example programs and a few benchmark programs from the SPLASH-2 suite.

关键词： Programming profession Yarn Microprocessors Workstations Sun Concurrent computing Laboratories Fuels Oceans Drugs

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parallel algorithms for simultaneous scheduling, binding and floorplanning in high-level synthesis

Parallel algorithms for simultaneous scheduling, binding and...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： P. Prabhakaran P. Banerjee Center for Reliable and High-Performance Computing Coordinated Science Laboratory University of Illinois Urbana-Champaign IL USA Center for Parallel and Distributed Computing Department of Electrical and Computer Engineering Northwestern University Evanston IL USA

With small device features in submicron technologies, interconnection delays play a dominant part in cycle time. Hence, it is important to consider the impact of physical design during high level synthesis. In comparison to a traditional approach which separates high-level synthesis from physical design, an algorithm which is able to make these stages interact very closely, would result in solutions with lower latency and area. However, such an approach could result in increased runtimes. parallel processing is an attractive way of reducing the runtimes. In this paper, two parallel algorithms for simultaneous scheduling, binding and floorplanning algorithm are presented. A detailed hardware model is considered, taking into account multiplexor and register areas and delays. Experimental results are reported on an IBM SP-2 multicomputer, with close to linear speedups for a set of benchmark circuits.

关键词： parallel algorithms High level synthesis Runtime Integrated circuit interconnections Delay effects Algorithm design and analysis parallel processing Scheduling algorithm Hardware Registers

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A mathematical model, heuristic, and simulation study for a basic data staging problem in a heterogeneous networking environment

A mathematical model, heuristic, and simulation study for a ...

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Heterogeneous Computing Workshop

作者： Min Tan M.D. Theys H.J. Siegel N.B. Beck M. Jurczyk Cisco Systems Inc. San Jose CA USA Parallel Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Computer Engineering and Computer Science University of Missouri Columbia Columbia MO USA

Data staging is an important data management problem for a distributed heterogeneous networking environment, where each data storage location and intermediate node may have specific data available, storage limitations, and communication links. Sites in the network request data items and each item is associated with a specific deadline and priority. It is assumed that not all requests can be satisfied by their deadline. The work concentrates on solving a basic version of the data staging problem in which all parameter values for the communication system and the data request information represent the best known information collected so far and stay fixed throughout the scheduling process. A mathematical model for the basic data staging problem is introduced. Then, a multiple-source shortest-path algorithm based heuristic for finding a suboptimal schedule of the communication steps for data staging is presented. A simulation study is provided, which evaluates the performance of the proposed heuristic. The results show the advantages of the proposed heuristic over two random based scheduling techniques. This research, based on the simplified static model, serves as a necessary step toward solving the more realistic and complicated version of the data staging problem involving dynamic scheduling, fault tolerance, and determining where to stage data.

关键词： Mathematical model computer networks distributed computing Data engineering Military computing Intelligent networks computer network management Environmental management Memory Satellite broadcasting

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Monitoring functions on global states of distributed programs

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JOURNAL OF parallel AND distributed COMPUTING 1997年第2期41卷 173-189页

作者： Tomlinson, AI Garg, VK Parallel and Distributed Systems Laboratory Department of Electrical and Computer Engineering 4 The University of Texas at Austin Austin Texas 78712

The domain of a global function is the set of all global states of an execution of a distributed program, We show how to monitor a program in order to determine if there exists a global state in which the sum x(1) + x(2) +...+ x(N), exceeds some constant K, where x(i) is defined in process i. We examine the cases where x(i) is an integer variable for N = 2 and where x(i) is a boolean variable for general N, For both cases we provide algorithms, prove their correctness, and analyze their complexity. (C) 1997 Academic Press.

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Using the causal domain to specify and verify distributed programs

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ACTA INFORMATICA 1997年第9期34卷 667-686页

作者： Garg, VK Tomlinson, AI Parallel and Distributed Systems Laboratory Department of Electrical and Computer Engineering The University of Texas at Austin Austin TX 78712 USA (http://maple.ece.utexas.edu) US

A system for specification and proof of distributed programs is presented. The method is based directly on the partial order of local states (poset) and avoids the notions of time and simultaneity. Programs are specified by documenting the relationship between local states which are adjacent to each other in the poset. Program properties are defined by stating properties of the poset. Many program properties can be expressed succinctly and elegantly using this method because poset properties inherently account for varying processor execution speeds. The system utilizes a proof technique which uses induction on the complement of the causally precedes relation and is shown to be useful in proving poset properties. We demonstrate the system on three example algorithms: vector clocks, mutual exclusion, and direct dependency clocks.

关键词： ALGORITHMS PARTIALLY ordered sets

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COMPILE TIME PARTITIONING OF NESTED LOOP ITERATION SPACES WITH NON-UNIFORM DEPENDENCES*

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parallel Algorithms and Applications 1997年第1-3期12卷 113-141页

作者： Swamy Punyamurtul - AMD Austin TX-78741 swamy@***[a] Vipin Chaudhary[a] Jialin Ju[a] Sumit Roy[a] [a] Dept. of Electrical and Computer Engineering Parallel and Distributed Computing Laboratory Detroit 48202

In this paper we address the problem of partitioning nested loops with non-uniform (irregular) dependence vectors. parallelizing and partitioning of nested loops requires efficient inter-iteration dependence analysis. Although many methods exist for nested loop partitioning, most of these perform poorly when parallelizing nested loops with irregular dependences. Unlike the case of nested loops with uniform dependences these will have a complicated dependence pattern which forms a non-uniform dependence vector set. We apply the results of classical convex theory and principles of linear programming to iteration spaces and show the correspondence between minimum dependence distance computation and iteration space tiling. Cross-iteration dependences are analyzed by forming an Integer Dependence Convex Hull (IDCH). Every integer point in this IDCH corresponds to a dependence vector in the iteration space of the nested loops. A simple way to compute minimum dependence distances from the dependence distance vectors of the extreme points of the IDCH is presented. Using these minimum dependence distances the iteration space can be tiled. Iterations within a tile can be executed in parallel and the different tiles can then be executed with proper synchronization. We demonstrate that our technique gives much better speedup and extracts more parallelism than the existing techniques.

关键词： nested loops partitioning Integer Dependence Convex

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