Multithreaded approach for dynamic load balancing of parallel adaptive PDE computations

We present a multithreaded model for the dynamic load-balancing of parallel adaptive PDE computations. Multithreading is used as a means of exploring concurrency in the processor level and for tolerating: (i) long memory latencies, and (ii) synchronization costs inherent to traditional load-balancing methods. We show that under certain values of the parameters (i.e., number of threads, and context switch time) of the model, multithreaded load-balancing systems are expected to perform better than existing software systems based on traditional load-balancing methods.