Introduction to algorithms
Parallel programming with MPI
On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Heuristic Algorithms for Scheduling Independent Tasks on Nonidentical Processors
Journal of the ACM (JACM)
Dynamic mapping of a class of independent tasks onto heterogeneous computing systems
Journal of Parallel and Distributed Computing - Special issue on software support for distributed computing
SETI@HOME—massively distributed computing for SETI
Computing in Science and Engineering
Efficient load balancing for wide-area divide-and-conquer applications
PPoPP '01 Proceedings of the eighth ACM SIGPLAN symposium on Principles and practices of parallel programming
PPoPP '01 Proceedings of the eighth ACM SIGPLAN symposium on Principles and practices of parallel programming
On the origin of power laws in Internet topologies
ACM SIGCOMM Computer Communication Review
Journal of Parallel and Distributed Computing
Parallel Computer Architecture: A Hardware/Software Approach
Parallel Computer Architecture: A Hardware/Software Approach
High-Performance Algorithm Engineering for Computational Phylogenetics
The Journal of Supercomputing - Special issue on computational issues in fluid dynamics optimization and simulation
Scheduling Strategies for Master-Slave Tasking on Heterogeneous Processor Grids
PARA '02 Proceedings of the 6th International Conference on Applied Parallel Computing Advanced Scientific Computing
ICDCS '99 Workshop on Self-stabilizing Systems
Bandwidth-Centric Allocation of Independent Tasks on Heterogeneous Platforms
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Scheduling Multi-Component Applications in Heterogeneous Wide-Area Networks
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
Master/Slave Computing on the Grid
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
A Heuristic Algorithm for Mapping Communicating Tasks on Heterogeneous Resources
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
Grid Computing: Making the Global Infrastructure a Reality
Grid Computing: Making the Global Infrastructure a Reality
Scheduling Strategies for Master-Slave Tasking on Heterogeneous Processor Platforms
IEEE Transactions on Parallel and Distributed Systems
ISPDC '04 Proceedings of the Third International Symposium on Parallel and Distributed Computing/Third International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Networks
The GrADS Project: Software Support for High-Level Grid Application Development
International Journal of High Performance Computing Applications
Liana: a decentralized load-dependent scheduler for performance-cost optimization of grid service
The Journal of Supercomputing
Toward a fully decentralized algorithm for multiple bag-of-tasks application scheduling on grids
GRID '08 Proceedings of the 2008 9th IEEE/ACM International Conference on Grid Computing
Energy-Aware Scheduling of Flow Applications on Master-Worker Platforms
Euro-Par '09 Proceedings of the 15th International Euro-Par Conference on Parallel Processing
Microprocessors & Microsystems
Reliability and performance optimization of pipelined real-time systems
Journal of Parallel and Distributed Computing
Fair scheduling of bag-of-tasks applications using distributed Lagrangian optimization
Journal of Parallel and Distributed Computing
| Hi-index | 0.00 |
In this paper, we consider the task allocation problem for computing a large set of equal-sized independent tasks on a heterogeneous computing system where the tasks initially reside on a single computer (the root) in the system. This problem represents the computation paradigm for a wide range of applications such as SETI@home and Monte Carlo simulations. We consider the scenario where the systems have a general graph-structured topology, and the computers are capable of concurrent communications and overlapping communications with computation. We show that the maximization of system throughput reduces to a standard network flow problem. We then develop a decentralized adaptive algorithm that solves a relaxed form of the standard network flow problem and maximizes the system throughput. This algorithm is then approximated by a simple decentralized protocol to coordinate the resources adaptively. Simulations are conducted to verify the effectiveness of the proposed approach. For both uniformly distributed and power law distributed systems, close-to-optimal throughput is achieved and improved performance over a bandwidth-centric heuristic is observed. The adaptivity of the proposed approach is also verified through simulations.