Job Scheduling Strategies for Parallel Processing :
Feitelson, Dror G.
Job Scheduling Strategies for Parallel Processing : 10th International Workshop, JSSPP 2004, New York, NY, USA, June 13, 2004. Revised Selected Papers / edited by Dror G. Feitelson, Larry Rudolph, Uwe Schwiegelshohn. - viii, 317 páginas Also available online. recurso en línea. - Lecture Notes in Computer Science, 3277 0302-9743 ; .
Springer eBooks
Parallel Job Scheduling — A Status Report -- Scheduling on the Top 50 Machines -- Parallel Computer Workload Modeling with Markov Chains -- Enhancements to the Decision Process of the Self-Tuning dynP Scheduler -- Reconfigurable Gang Scheduling Algorithm -- Time-Critical Scheduling on a Well Utilised HPC System at ECMWF Using Loadleveler with Resource Reservation -- Inferring the Topology and Traffic Load of Parallel Programs Running in a Virtual Machine Environment -- Multi-toroidal Interconnects: Using Additional Communication Links to Improve Utilization of Parallel Computers -- Costs and Benefits of Load Sharing in the Computational Grid -- Workload Characteristics of a Multi-cluster Supercomputer -- A Dynamic Co-allocation Service in Multicluster Systems -- Exploiting Replication and Data Reuse to Efficiently Schedule Data-Intensive Applications on Grids -- Performance Implications of Failures in Large-Scale Cluster Scheduling -- Are User Runtime Estimates Inherently Inaccurate? -- Improving Speedup and Response Times by Replicating Parallel Programs on a SNOW -- LOMARC — Lookahead Matchmaking for Multi-resource Coscheduling.
This book constitutes the thoroughly refereed postproceedings of the 10th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2004, held in New York, NY in June 2004. The 15 revised full research papers presented together with a report on scheduling on the Top 50 machines went through two rounds of reviewing and improvement. Various current issues in job scheduling and load balancing are addressed in the context of computing clusters, parallel and distributed systems, multi-processor systems, and supercomputers.
9783540317951
10.1007/b107134 doi
QA76.76.O63
Job Scheduling Strategies for Parallel Processing : 10th International Workshop, JSSPP 2004, New York, NY, USA, June 13, 2004. Revised Selected Papers / edited by Dror G. Feitelson, Larry Rudolph, Uwe Schwiegelshohn. - viii, 317 páginas Also available online. recurso en línea. - Lecture Notes in Computer Science, 3277 0302-9743 ; .
Springer eBooks
Parallel Job Scheduling — A Status Report -- Scheduling on the Top 50 Machines -- Parallel Computer Workload Modeling with Markov Chains -- Enhancements to the Decision Process of the Self-Tuning dynP Scheduler -- Reconfigurable Gang Scheduling Algorithm -- Time-Critical Scheduling on a Well Utilised HPC System at ECMWF Using Loadleveler with Resource Reservation -- Inferring the Topology and Traffic Load of Parallel Programs Running in a Virtual Machine Environment -- Multi-toroidal Interconnects: Using Additional Communication Links to Improve Utilization of Parallel Computers -- Costs and Benefits of Load Sharing in the Computational Grid -- Workload Characteristics of a Multi-cluster Supercomputer -- A Dynamic Co-allocation Service in Multicluster Systems -- Exploiting Replication and Data Reuse to Efficiently Schedule Data-Intensive Applications on Grids -- Performance Implications of Failures in Large-Scale Cluster Scheduling -- Are User Runtime Estimates Inherently Inaccurate? -- Improving Speedup and Response Times by Replicating Parallel Programs on a SNOW -- LOMARC — Lookahead Matchmaking for Multi-resource Coscheduling.
This book constitutes the thoroughly refereed postproceedings of the 10th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2004, held in New York, NY in June 2004. The 15 revised full research papers presented together with a report on scheduling on the Top 50 machines went through two rounds of reviewing and improvement. Various current issues in job scheduling and load balancing are addressed in the context of computing clusters, parallel and distributed systems, multi-processor systems, and supercomputers.
9783540317951
10.1007/b107134 doi
QA76.76.O63