Grid
Grid definitions
Carl Kesselman and Ian Foster define grid as follows:
1998/99 A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities.
Grid has to fulfill following three points:2001 ... coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organizations.
- coordinates resources that are not under centralized management
- use standard, open, generic protocols and interfaces
- provides non-trivial quality of services (more than each individual part of its own)
2002 ...a Grid is a system that: coordinates resources that are not subject to centralized control … using standard, open, general-purpose protocols and interfaces … to deliver nontrivial qualities of service …
Computational grid is described by analogy with electrical power network - around year 1910 every electrified building had its own electricity generator but those generators were not interconnected. There was no possibility to use larger capacity than capacity of a single generator, total capacity of all generators were not used effectively and establishment of electricity was expensive. The real utilization of electricity usage begun after start of interconnected large power stations and distribution network to the consumers. This allowed cheap, ubiquitous and standardized source of electric power. Similarly, every organization today manages its own computational capacities (computers, disc capacity, software, data, specialized hardware) that can not be effectively shared with others. Computational grid should enable such effective sharing of computational capacities among organizations.
Features- Heterogeneous hardware and software
- Loosely-coupled machines
- Potentially unreliable low-speed network
- Several distributed locations
- Several administrative domains
- Potentially insecure
- Grid middleware (ARC, gLite, etc.)
- Best for embarrassingly parallel jobs
- Focus on high throughput / capacity computing
Scientific Areas of Interest Mostly Computational Sciences
- Computer Science
- Computational Chemistry, Cheminformatics
- Bioinformatics, Biomedical Computing (e.g., Imaging)
- Physics (High Energy Physics, Plasma Physics, Solid State Physics, Theoretical Physics, QCD, etc.)
- Earth Observation, Satellite Imaging, Meteorology, Climatology, Geography, Geology, etc.
- Nanotechnology
- Many more
- Financial Analysis
- Digital Libraries
- Knowledge Grids