Load balancing and fault tolerance in applicative systems

Applicative systems are promising candidates to achieve high performance computing through aggregation of processors. This dissertation studies two important issues in building scalable applicative systems: load balancing problem and fault tolerance.; A dynamic load balancing scheme is proposed for large scale applicative systems. The method is based on a demand-driven approach, the gradient model, which transfers excessive tasks to the nearest idle processor via a gradient surface. The gradient surface is established by the demands from idle processors. The algorithm is fully distributed and asynchronous. A global balance is achieved by successive refinements of many localized balances. The gradient model is independent of system topology and can easily accommodate heterogeneous multiprocessor systems. Simulations have shown that the gradient model performs reasonably well.; The concept of functional checkpointing is proposed as the nucleus of a distributed recovery mechanism. This entails incrementally building a resilient structure as the evaluation of an applicative program proceeds. A simple rollback algorithm is suggested to regenerate the corrupted structure by the most effective functional checkpoints. Another algorithm, which attempts to recover all intermediate results, is also presented. The parent of a faulty task reproduces a functional twin of the failed task. The regenerated task inherits all offspring of the faulty task so that partial results can be salvaged.