Scheduling in multiprogrammed parallel systems
SIGMETRICS '88 Proceedings of the 1988 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Process control and scheduling issues for multiprogrammed shared-memory multiprocessors
SOSP '89 Proceedings of the twelfth ACM symposium on Operating systems principles
Characterizations of parallelism in applications and their use in scheduling
SIGMETRICS '89 Proceedings of the 1989 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Processor scheduling in shared memory multiprocessors
SIGMETRICS '90 Proceedings of the 1990 ACM SIGMETRICS conference on Measurement and modeling of computer systems
The performance of multiprogrammed multiprocessor scheduling algorithms
SIGMETRICS '90 Proceedings of the 1990 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Algorithms for scalable synchronization on shared-memory multiprocessors
ACM Transactions on Computer Systems (TOCS)
A dynamic processor allocation policy for multiprogrammed shared-memory multiprocessors
ACM Transactions on Computer Systems (TOCS)
Application scheduling and processor allocation in multiprogrammed parallel processing systems
Performance Evaluation - Special issue: performance modeling of parallel processing systems
SIGMETRICS '94 Proceedings of the 1994 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Performance benefits and limitations and limitations of large NUMA multiprocessors
Performance '93 Proceedings of the 16th IFIP Working Group 7.3 international symposium on Computer performance modeling measurement and evaluation
A Hierarchical Task Queue Organization for Shared-Memory Multiprocessor Systems
IEEE Transactions on Parallel and Distributed Systems
Job Characteristics of a Production Parallel Scientivic Workload on the NASA Ames iPSC/860
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Parallel Job Scheduling: Issues and Approaches
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Workload Evolution on the Cornell Theory Center IBM SP2
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Towards Convergence in Job Schedulers for Parallel Supercomputers
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Theory and Practice in Parallel Job Scheduling
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
Hierarchical Architecture for Parallel Query Processing on Networks of Workstations
HIPC '98 Proceedings of the Fifth International Conference on High Performance Computing
A Hierarchical Processor Scheduling Policy for Distributed-Memory Multicomputer Systems
HIPC '97 Proceedings of the Fourth International Conference on High-Performance Computing
An Efficient Adaptive Scheduling Scheme for Distributed Memory Multicomputers
IEEE Transactions on Parallel and Distributed Systems
Performance of adaptive space-sharing policies in dedicated heterogeneous cluster systems
Future Generation Computer Systems - Special issue: Computational chemistry and molecular dynamics
Performance Evaluation of Task Pools Based on Hardware Synchronization
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
The design and implementation of LilyTask in shared memory
ACM SIGOPS Operating Systems Review
Automatic Middleware Deployment Planning On Clusters
International Journal of High Performance Computing Applications
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Processor scheduling policies for multiprocessor systems can be broadly divided into space-sharing and time-sharing policies. Space-sharing policies divide the system processors into a number of partitions and each partition is exclusively allocated to a single job. In time-sharing policies, processors are temporally shared by jobs. Several space-sharing and time-sharing policies have been proposed for small-scale shared-memory systems and require a central run queue and/or central scheduler. The central queue/scheduler poses serious scalability problems for large-scale multiprocessor systems. Furthermore, space-sharing and time-sharing policies have their advantages and disadvantages. In this paper, we propose a new multiprocessor scheduling policy that eliminates contention for the central queue/scheduler. Our hierarchical scheduling policy (HSP) is a self-scheduling policy and uses a hierarchical run queue organization to facilitate processor allocation to jobs. We show that the HSP policy is considerably better than purely space-sharing and purely time-sharing policies over a wide range of system and workload parameters of interest.