A Fast Recognition-Complete Processor Allocation Strategy for Hypercube Computers
IEEE Transactions on Computers
MPI: a message passing interface
Proceedings of the 1993 ACM/IEEE conference on Supercomputing
The interaction of parallel and sequential workloads on a network of workstations
Proceedings of the 1995 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
A worldwide flock of Condors: load sharing among workstation clusters
Future Generation Computer Systems - Special issue: resource management in distributed systems
The utility of exploiting idle workstations for parallel computation
SIGMETRICS '97 Proceedings of the 1997 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Linger Longer: fine-grain cycle stealing for networks of workstations
SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
The MOSIX Distributed Operating System: Load Balancing for UNIX
The MOSIX Distributed Operating System: Load Balancing for UNIX
Batrun: Utilizing Idle Workstations for Large-Scale Computing
IEEE Parallel & Distributed Technology: Systems & Technology
Dynamic balancing complex workload in workstation networks - challenge, concepts and experience
HPCN Europe '95 Proceedings of the International Conference and Exhibition on High-Performance Computing and Networking
Characterizing NAS Benchmark Performance on Shared Heterogeneous Networks
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
A Comparative Evaluation of Implicit Coscheduling Strategies for Networks of Workstations
HPDC '00 Proceedings of the 9th IEEE International Symposium on High Performance Distributed Computing
Computer
ICPADS '05 Proceedings of the 11th International Conference on Parallel and Distributed Systems - Volume 01
A space and time sharing scheduling approach for PVM non-dedicated clusters
PVM/MPI'05 Proceedings of the 12th European PVM/MPI users' group conference on Recent Advances in Parallel Virtual Machine and Message Passing Interface
ISPA'04 Proceedings of the Second international conference on Parallel and Distributed Processing and Applications
Concurrent execution of multiple NAS parallel programs on a cluster
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part I
Developing the KMKE knowledge management system based on design patterns and parallel processing
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
On/off-line prediction applied to job scheduling on non-dedicated NOWs
Journal of Computer Science and Technology - Special issue on natural language processing
State-based predictions with self-correction on Enterprise Desktop Grid environments
Journal of Parallel and Distributed Computing
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Computers of a non-dedicated cluster are often idle (users attend meetings, have lunch or coffee breaks) or lightly loaded (users carry out simple computations to support problem solving activities). These underutilised computers can be employed to execute parallel applications. Thus, these computers can be shared by parallel and sequential applications, which could lead to the improvement of their execution performance. However, there is a lack of experimental study showing the applications' performance and the system utilization of executing parallel and sequential applications concurrently and concurrent execution of multiple parallel applications on a non-dedicated cluster. Here we present the result of an experimental study into load balancing based scheduling of mixtures of NAS Parallel Benchmarks and BYTE sequential applications on a very low cost non-dedicated cluster. This study showed that the proposed sharing provided performance boost as compared to the execution of the parallel load in isolation on a reduced number of computers and better cluster utilization. The results of this research were used not only to validate other researchers' result generated by simulation but also to support our research mission of widening the use of non-dedicated clusters. Our promising results obtained could promote further research studies to convince universities, business and industry, which require a large amount of computing resources, to run parallel applications on their already owned non-dedicated clusters.