Harness: a next generation distributed virtual machine
Future Generation Computer Systems - Special issue on metacomputing
Algorithm 806: SPRNG: a scalable library for pseudorandom number generation
ACM Transactions on Mathematical Software (TOMS)
SETI@HOME—massively distributed computing for SETI
Computing in Science and Engineering
Architectural Models for Resource Management in the Grid
GRID '00 Proceedings of the First IEEE/ACM International Workshop on Grid Computing
Sabotage-Tolerance Mechanisms for Volunteer Computing Systems
CCGRID '01 Proceedings of the 1st International Symposium on Cluster Computing and the Grid
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
A grid workflow-based Monte Carlo simulation environment
Neural, Parallel & Scientific Computations - Special issue: Grid computing
Trustworthy remote compiling services for grid-based scientific applications
The Journal of Supercomputing
Monte Carlo methods for matrix computations on the grid
Future Generation Computer Systems
GridMD: program architecture for distributed molecular simulation
ICA3PP'05 Proceedings of the 6th international conference on Algorithms and Architectures for Parallel Processing
Concurrency and Computation: Practice & Experience
| Hi-index | 0.00 |
Monte Carlo applications are widely perceived as computationally intensive but naturally parallel. Therefore, they can be effectively executed on the grid using the dynamic bag-of-work model. We improve the efficiency of the subtask-scheduling scheme by using an N-out-of-M strategy, and develop a Monte Carlo-specific lightweight checkpoint technique, which leads to a performance improvement for Monte Carlo grid computing. Also, we enhance the trustworthiness of Monte Carlo grid-computing applications by utilizing the statistical nature of Monte Carlo and by cryptographically validating intermediate results utilizing the random number generator already in use in the Monte Carlo application. All these techniques lead to a high-performance grid-computing infrastructure that is capable of providing trustworthy Monte Carlo computation services.