Behavioural model debugging in Linda

This thesis investigates event-based behavioural model debugging in Linda. A study is presented of the Linda parallel programming paradigm, its amenability to debugging, and a model for debugging Linda programs using Milner's CCS. In support of the construction of expected behaviour models, a Linda program specification language is proposed. A behaviour recognition engine that is based on such specifications is also discussed. It is shown that Linda's distinctive characteristics make it amenable to debugging without the usual problems associated with paraUel debuggers. Furthermore, it is shown that a behavioural model debugger, based on the proposed specification language, effectively exploits the debugging opportunity. The ideas developed in the thesis are demonstrated in an experimental Modula-2 Linda system

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