Performance Analysis and Grid Computing: Selected Articles from the Workshop on Performance Analysis and Distributed Computing August 19–23, 2002, Dagstuhl, Germany
Vladimir Getov, Michael Gerndt, Adolfy Hoisie, Allen Malony, Barton Miller
Springer Science & Business Media, Nov 30, 2003 - Computers - 290 pages
Past and current research in computer performance analysis has focused primarily on dedicated parallel machines. However, future applications in the area of high-performance computing will not only use individual parallel systems but a large set of networked resources. This scenario of computational and data Grids is attracting a great deal of attention from both computer and computational scientists. In addition to the inherent complexity of parallel machines, the sharing and transparency of the available resources introduces new challenges on performance analysis, techniques, and systems. In order to meet those challenges, a multi-disciplinary approach to the multi-faceted problems of performance is required. New degrees of freedom will come into play with a direct impact on the performance of Grid computing, including wide-area network performance, quality-of-service (QoS), heterogeneity, and middleware systems, to mention only a few.
Reflecting this new reality, the Dagstuhl Workshop on Performance Analysis and Distributed Computing, organized by members of the European Working Group APART, was designed to bring together researchers from both the high-performance computing and the distributed computing areas. Indeed, attendees with expertise in a variety of topics in computer and computational sciences arrived in Dagstuhl at the end of August 2002 to discuss the state-of-the-art and the future of computer performance research as it applies to systems, applications, and Grids.
Performance Analysis and Grid Computing comprises selected contributions encapsulating this scientifically rich event. The articles are organized in three parts: Performance Modeling and Analysis, Performance Tools and Systems, and Grid Performance and Applications. It will provide invaluable reading for researchers and developers in the areas of performance analysis, high-end computer systems, and Grid computing.
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DIFFERENT APPROACHES TO AUTOMATIC PERFORMANCE ANALYSIS OF DISTRIBUTED APPLICATIONS
PERFORMANCE MODELING OF DETERMINISTIC TRANSPORT COMPUTATIONS
PERFORMANCE OPTIMIZATION OF RK METHODS USING BLOCKBASED PIPELINING
PERFORMANCE EVALUATION OF HYBRID PARALLEL PROGRAMMING PARADIGMS
PERFORMANCE MODELLING FOR TASKPARALLEL PROGRAMS
COLLECTIVE COMMUNICATION PATTERNS ON THE QUADRICS NETWORK
PERFORMANCE TOOLS AND SYSTEMS
THE DESIGN OF A PERFORMANCE STEERING SYSTEM FOR COMPONENTBASED GRID APPLICATIONS
DYNAMIC INSTRUMENTATION FOR JAVA USING A VIRTUAL JVM
A PERFORMANCE ANALYSIS TOOL FOR PARALLEL AND DISTRIBUTED APPLICATIONS
GRID PERFORMANCE AND APPLICATIONS
COMMERCIAL APPLICATIONS OF GRID COMPUTING
MESH GENERATION AND OPTIMISTIC COMPUTATION ON THE GRID
GRID PERFORMANCE AND RESOURCE MANAGEMENT USING MOBILE AGENTS
MONITORING OF INTERACTIVE GRID APPLICATIONS
THE UNICORE GRID AND ITS OPTIONS FOR PERFORMANCE ANALYSIS
Other editions - View all
Aksum algorithm Analyzer approach architecture automatic performance analysis bandwidth barrier behavior blocks bottlenecks broadcast buffer cache callpath cluster code region collective communication communication operations component Computer Science configuration data parallel developed evaluation execution Figure framework function G-PM Global Grid Forum Grid applications Grid computing Grid environment Grid Services hardware hybrid IEEE implementation interaction interface iteration Java latency load balancing machine mance master thread memory metrics mobile agent modules monitoring MPI processes multicast nodes OCM-G ODE systems OpenMP optimal optimistic overhead Parallel and Distributed Parallel Computing parallel programs parameters performance analysis performance analysis tool performance data performance measurement performance models performance properties performance steering system performance tools pipeline pipelined computation prediction processor QsNET Quadrics requests RK method runtime formulas scalability Section servers specific stage vector synchronization tion UNICORE visualization Web caching WSDL