Remora : implementing adaptive parallelism on a heterogeneous cluster of networked workstations

Computers connected to a local area network are often only fully utilized for short periods of time. In fact, most workstations are not used at all for a significant portion of the day. The combined "idle time" of the workstations on a network constitutes a significant computing resource, which is generally wasted. If harnessed properly, such a resource could constitute a cheap alternative to expensive high-performance computers. Adaptive parallelism refers to the parallel execution of a computation on a dynamically changing set of processors. This thesis investigates the viability of this approach as a vehicle to harness the "idle cycles" available on a heterogeneous cluster of networked computers. A system, called Remora, which implements adaptive parallelism via the Linda programming paradigm, is presented. Experiments, performed using Remora, show that adaptive parallelism provides an efficient vehicle for using idle processor cycles, without having an adverse effect on the tasks which constitute the normal workload of the computers being used

A Software Platform for Constructing Scientific Applications from Heterogeneous Resources

Support for heterogeneous processing is useful for increasing the functionality available to designers of scientific applications. For example, rather than implement an application requiring remote vector processing and local visualization as two separate programs, such support allows an alternative structure in which the application is a single logical program with transparent transfer of control and data between phases. In addition to being simpler and more intuitive, such structuring makes it feasible to enhance the way in which users interact with the application to do, for instance, model steering. Here, a software platform that facilitates the construction of this type of scientific application is described. Its key component is Schooner, an interconnection system that includes an intermediate data representation, a simple specification language, and a heterogeneous remote procedure call (RPC) facility; to provide sophisticated visualization capabilities and an execution framewor..

An efficient parallelization of a real scientific application

Bibliography: leaves 137-145.In the past decade the cost of computing has come down considerably making high-powered computing more easily affordable. As a result many institutions and organisations now have networks of high-powered workstations. Such networks provide a large, generally untapped, source of computing power which can be used for running large scientific applications which previously could only be run on supercomputers. This dissertation shows that a substantial improvement in performance can be achieved by the parallelization of a real scientific application for a heterogeneous network of Sun and Silicon Graphics workstations connected by an Ethernet network, but that this is affected by a number of factors. These factors include communication delays, load balancing, and the number of slaves used. This dissertation shows that performance can be improved by sending more, shorter messages, and by overlapping communication with computation. Part of this thesis concerns the difficulties involved in the evaluation of parallel performance on a heterogeneous network. This dissertation shows that conventional methods such as speedup and efficiency are not appropriate for evaluating the performance of a heterogeneous system, and that linear speed gives a much more representative indication of the actual performance achieved. We also proposed new concepts of perfect linear speed and linear efficiency, which help to evaluate the improvement in parallel performance on a heterogeneous system