28 research outputs found
Visual Programming: Concepts and Implementations
The computing environment has changed dramatically since the advent of the computer. Enhanced computer graphics and sheer processing power have ushered in a new age of computing. User interfaces have advanced from simple line entry to powerful graphical interfaces. With these advances, computer languages are no longer forced to be sequentially and textually-based. A new programming paradigm has evolved to harness the power of today's computing environment - visual programming. Visual programming provides the user with visible models which reflect physical objects. By connecting these visible models to each other, an executable program is created. By removing the inherent abstractions of textual languages, visual programming could lead computing into a new era
Parallel processing for scientific computations
The scope of this project dealt with the investigation of the requirements to support distributed computing of scientific computations over a cluster of cooperative workstations. Various experiments on computations for the solution of simultaneous linear equations were performed in the early phase of the project to gain experience in the general nature and requirements of scientific applications. A specification of a distributed integrated computing environment, DICE, based on a distributed shared memory communication paradigm has been developed and evaluated. The distributed shared memory model facilitates porting existing parallel algorithms that have been designed for shared memory multiprocessor systems to the new environment. The potential of this new environment is to provide supercomputing capability through the utilization of the aggregate power of workstations cooperating in a cluster interconnected via a local area network. Workstations, generally, do not have the computing power to tackle complex scientific applications, making them primarily useful for visualization, data reduction, and filtering as far as complex scientific applications are concerned. There is a tremendous amount of computing power that is left unused in a network of workstations. Very often a workstation is simply sitting idle on a desk. A set of tools can be developed to take advantage of this potential computing power to create a platform suitable for large scientific computations. The integration of several workstations into a logical cluster of distributed, cooperative, computing stations presents an alternative to shared memory multiprocessor systems. In this project we designed and evaluated such a system