Large-Scale Scientific Computing: Third International Conference, LSSC 2001 Sozopol, Bulgaria, June 6–10, 2001 Revised Papers

The construction of efficient iterative linear equation solvers for ill-conditioned general symmetric positive definite systems is discussed. Certain known two-level conjugate gradient preconditioning techniques are presented in a uniform way and are further generalized and optimized with respect to the spectral or the K-condition numbers. The resulting constructions have shown to be useful for the solution of largescale ill-conditioned symmetric positive definite linear systems.

[1]  George C. Necula,et al.  Safe kernel extensions without run-time checking , 1996, OSDI '96.

[2]  Satoshi Matsuoka,et al.  Overview of a performance evaluation system for global computing scheduling algorithms , 1999, Proceedings. The Eighth International Symposium on High Performance Distributed Computing (Cat. No.99TH8469).

[3]  H. Faure Discrépance de suites associées à un système de numération (en dimension s) , 1982 .

[4]  Ian Goldberg,et al.  A secure environment for untrusted helper applications confining the Wily Hacker , 1996 .

[5]  J. Halton On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals , 1960 .

[6]  Gilles Fedak,et al.  XtremWeb: Building an Experimental Platform for Global Computing , 2000, GRID.

[7]  Andy Oram,et al.  Peer-to-Peer: Harnessing the Power of Disruptive Technologies , 2001 .

[8]  Michael Mascagni,et al.  Matrix Computations Using Quasirandom Sequences , 2000, NAA.

[9]  Crispan Cowan,et al.  StackGuard: Automatic Adaptive Detection and Prevention of Buffer-Overflow Attacks , 1998, USENIX Security Symposium.

[10]  Harald Niederreiter,et al.  Random number generation and Quasi-Monte Carlo methods , 1992, CBMS-NSF regional conference series in applied mathematics.

[11]  Gregor von Laszewski,et al.  CoG kits: a bridge between commodity distributed computing and high-performance grids , 2000, JAVA '00.

[12]  Aneta Karaivanova,et al.  Iterative Monte Carlo Algorithms for Linear Algebra Problems , 1996, WNAA.

[13]  Arnold L. Rosenberg Guidelines for Data-Parallel Cycle-Stealing in Networks of Workstations I: On Maximizing Expected Output , 1999, J. Parallel Distributed Comput..

[14]  J. Halton Sequential monte carlo techniques for the solution of linear systems , 1994 .

[15]  Peter R. Cappello,et al.  Javelin: Internet‐based parallel computing using Java , 1997 .

[16]  Satoshi Hirano,et al.  Towards Bayanihan: building an extensible framework for volunteer computing using Java † , 1998 .

[17]  Gilles Fedak,et al.  XtremWeb: a generic global computing system , 2001, Proceedings First IEEE/ACM International Symposium on Cluster Computing and the Grid.

[18]  Robert Wahbe,et al.  Efficient software-based fault isolation , 1994, SOSP '93.

[19]  Ian T. Foster,et al.  The anatomy of the grid: enabling scalable virtual organizations , 2001, Proceedings First IEEE/ACM International Symposium on Cluster Computing and the Grid.

[20]  Peter R. Cappello,et al.  Javelin++: scalability issues in global computing , 1999, JAVA '99.

[21]  Arnold L. Rosenberg Optimal schedules for data-parallel cycle-stealing in networks of workstations (extended abstract) , 2000, SPAA '00.

[22]  David A. Wagner,et al.  A First Step Towards Automated Detection of Buffer Overrun Vulnerabilities , 2000, NDSS.

[23]  Jeff Dike,et al.  A user-mode port of the Linux kernel , 2000, Annual Linux Showcase & Conference.

[24]  Maarten van Steen,et al.  The globe infrastructure directory service , 2002, Comput. Commun..

[25]  N. Nisan,et al.  Globally distributed computation over the Internet-the POPCORN project , 1998, Proceedings. 18th International Conference on Distributed Computing Systems (Cat. No.98CB36183).

[26]  R. Wolski,et al.  Predicting the CPU availability of time‐shared Unix systems on the computational grid , 1999, Proceedings. The Eighth International Symposium on High Performance Distributed Computing (Cat. No.99TH8469).

[27]  R. Caflisch Monte Carlo and quasi-Monte Carlo methods , 1998, Acta Numerica.

[28]  R. F. Freund,et al.  Dynamic matching and scheduling of a class of independent tasks onto heterogeneous computing systems , 1999, Proceedings. Eighth Heterogeneous Computing Workshop (HCW'99).

[29]  Michael Mascagni,et al.  What Are Quasirandom Numbers And Are They Good For Anything Besides Integration , 2000 .

[30]  J. Hammersley,et al.  Monte Carlo Methods , 1966 .