Allocating Independent Subtasks on Parallel Processors
IEEE Transactions on Software Engineering
Guided self-scheduling: A practical scheduling scheme for parallel supercomputers
IEEE Transactions on Computers
Access normalization: loop restructuring for NUMA computers
ACM Transactions on Computer Systems (TOCS)
Using Processor Affinity in Loop Scheduling on Shared-Memory Multiprocessors
IEEE Transactions on Parallel and Distributed Systems
Loop scheduling for heterogeneity
HPDC '95 Proceedings of the 4th IEEE International Symposium on High Performance Distributed Computing
Dome: Parallel Programming in a Heterogeneous Multi-User Environment
Dome: Parallel Programming in a Heterogeneous Multi-User Environment
Customized Dynamic Load Balancing for a Network of Workstations
Customized Dynamic Load Balancing for a Network of Workstations
PADS '99 Proceedings of the thirteenth workshop on Parallel and distributed simulation
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Predicting the cost and benefit of adapting data parallel applications in clusters
Journal of Parallel and Distributed Computing
Using Disk Throughput Data in Predictions of End-to-End Grid Data Transfers
GRID '02 Proceedings of the Third International Workshop on Grid Computing
Predicting the Performance of Wide Area Data Transfers
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Dynamic Load Balancing of Iterative Data Parallel Problems on a Workstation Clustering
HPC-ASIA '97 Proceedings of the High-Performance Computing on the Information Superhighway, HPC-Asia '97
Predicting Sporadic Grid Data Transfers
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Using Regression Techniques to Predict Large Data Transfers
International Journal of High Performance Computing Applications
Scientific Programming - Distributed Computing and Applications
Performance of load balancing for grid computing
PDCN'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: parallel and distributed computing and networks
Data neighboring in local load balancing operations
ICCOMP'05 Proceedings of the 9th WSEAS International Conference on Computers
Multi-resource Load Optimization Strategy in Agent-Based Systems
KES-AMSTA '07 Proceedings of the 1st KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
Analysis and Experimentation of Grid-Based Data Mining with Dynamic Load Balancing
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Operating cost aware scheduling model for distributed servers based on global power pricing policies
COMPUTE '11 Proceedings of the Fourth Annual ACM Bangalore Conference
An enhanced load balancing mechanism based on deadline control on GridSim
Future Generation Computer Systems
Load balancing using mobile agent and a novel algorithm for updating load information partially
ICCNMC'05 Proceedings of the Third international conference on Networking and Mobile Computing
LoRDAS: a low-rate dos attack against application servers
CRITIS'07 Proceedings of the Second international conference on Critical Information Infrastructures Security
Heuristic static load-balancing algorithm applied to the fragment molecular orbital method
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
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Load balancing involves assigning to each processor work proportional to its performance, minimizing the execution time of the program. Although static load balancing can solve many problems (e.g., those caused by processor heterogeneity and non uniform loops) for most regular applications, the transient external load due to multiple users on a network of workstations necessitates a dynamic approach to load balancing. We examine the behavior of global vs. local, and centralized vs. distributed, load balancing strategies. We show that different schemes are best for different applications under varying program and system parameters. Therefore, customized load balancing schemes become essential for good performance. We present a hybrid compile time and run time modeling and decision process which selects (customizes) the best scheme, along with automatic generation of parallel code with calls to a run time library for load balancing.