Scheduling For Parallel Processing

To take full advantage of high performance computing, parallel applications must be carefully managed to guarantee quality of service and fairness in using shared resources. Scheduling for parallel computing is an interdisciplinary subject joining many fields, and the broadness of research yields an immense number and diversity of models for understanding scheduling problems.

This book presents scheduling models for parallel processing, problems defined on the grounds of certain scheduling models, and algorithms solving the scheduling problems. The book also provides helpful generalizations about scheduling models. This text will be valuable for researchers in parallel computing, operating systems, management science, and applied mathematics.

This book constitutes the thoroughly refereed post-conference proceedings of the 19th and 20th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2015 and 2016, held respectively in Hyderabad, India, on May 26, 2015 and in Chicago, IL, USA, on May 27, 2016.

This book constitutes the thoroughly refereed post-conference proceedings of the 22nd International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2018, held in Vancouver, Canada, in May 2018. The 7 revised full papers presented were carefully reviewed and selected from12 submissions. The papers cover topics in the fields of design and evaluation of new scheduling approaches. They focus on several interesting problems in resource management and scheduling.

This book constitutes the thoroughly refereed postproceedings of the 9th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2003, held in Seattle, Washington in June 2003 in conjunction with HPDC-12 and FFG-8. The 13 revised full papers presented were carefully refereed and selected during two rounds of reviewing and revision. The papers present state-of-the-art research results in the area with particular emphasis on conventional parallel systems (including infrastructure scheduling algorithms, I/O issues, and QoS), on scheduling issues in the context of grid computing, and on methodological aspects of performance evaluation in parallel job scheduling.