Valentin Kravtsov

TL;DR: The DataMiningGrid system provides tools and services facilitating the grid-enabling of data mining applications without any intervention on the application side and critical features of the system include flexibility, extensibility, scalability, efficiency, conceptual simplicity and ease of use.

TL;DR: The authors developed the DataMiningGrid system, which integrates a diverse set of programs and application scenarios within a single framework, and features scalability, flexible extensibility, sophisticated support for relevant standards and different users.

TL;DR: A simple, yet powerful, methodology for application-agnostic diagnostic and remediation of performance hot spots in elastic multi-tiered client/server applications, deployed as collections of black box Virtual Machines (VM).

TL;DR: The concept of topology-aware grid applications is derived from parallelized computational models of complex systems that are executed on heterogeneous resources, either because they require specialized hardware for certain calculations, or because their parallelization is flexible enough to exploit such resources.

TL;DR: This work designs architecture for a quasi-opportunistic supercomputer within the EU-supported project QosCosGrid, and presents the results obtained from studying and identifying the requirements a grid needs to meet in order to facilitate quasi- opportunistic supercomputing.