Data-intensive computing this approach is considered suitable for data-intensive computing and problems which are “embarrassingly parallel”, i.e. where it is relatively easy to separate the problem into a number of parallel tasks and there is no dependency or communication required between the tasks other than overall management of the tasks. These types of data processing problems are inherently adaptable to various forms of distributed computing including clusters, data grids, and cloud computing. Several common characteristics of data-intensive computing systems distinguish them from other forms of computing: A variety of system architectures have been implemented for data-intensive computing and large-scale data analysis applications
Analog image processing Analog image processing In electrical engineering and computer science, analog image processing is any image processing task conducted on two-dimensional analog signals by analog means (as opposed to digital image processing). Basically any data can be represented in two types named as 1.Analog 2.Digital if the pictorial representation of the data represented in analog wave formats that can be named as analog image. E.g.: television broadcasting in older days.. through the dish antenna systems.. Where as the digital representation or storing the data in digital form is termed as a digital image processing E.g.:image data stored in digital logic gates..