Supercomputing out of recycled garbage: preliminary experience with Piranha
ICS '92 Proceedings of the 6th international conference on Supercomputing
Supporting Fault-Tolerant Parallel Programming in Linda
IEEE Transactions on Parallel and Distributed Systems
The Mathematica book (3rd ed.)
The Mathematica book (3rd ed.)
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
CNS '97 Proceedings of the sixth annual conference on Computational neuroscience : trends in research, 1998: trends in research, 1998
Application-level scheduling on distributed heterogeneous networks
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
Applying NetSolve's Network-Enabled Server
IEEE Computational Science & Engineering
CALYPSO: a novel software system for fault-tolerant parallel processing on distributed platforms
HPDC '95 Proceedings of the 4th IEEE International Symposium on High Performance Distributed Computing
Portable checkpointing and recovery
HPDC '95 Proceedings of the 4th IEEE International Symposium on High Performance Distributed Computing
NetSolve version 1.2: Design and Implementation
NetSolve version 1.2: Design and Implementation
Client User''s Guide to NetSolve
Client User''s Guide to NetSolve
A Synopsis of the Legion Project
A Synopsis of the Legion Project
| Hi-index | 0.01 |
Scheduling in metacomputing environments is an active field of research as the vision of a Computational Grid becomes more concrete. An important class of Grid applications are long-running parallel computations with large numbers of somewhat independent tasks (Monte-Carlo simulations, parameter-space searches, etc.). A number of Grid middleware projects are available to implement such applications but scheduling strategies are still open research issues. This is mainly due to the diversity of both Grid resource types and of their availability patterns. The purpose of this work is to develop and validate a general adaptive scheduling algorithm for task farming applications along with a user interface that makes the algorithm accessible to domain scientists. Our algorithm is general in that it is not tailored to a particular Grid middleware and that it requires very few assumptions concerning the nature of the resources. Our first testbed is NetSolve as it allows quick and easy development of the algorithm by isolating the developer from issues such as process control, I/O, remote software access, or fault-tolerance.