Impact of Memory Contention on Dynamic Scheduling on Numa Multiprocessors

Self-scheduling is a method for task schedul ing in parallel programs, in which each processor acquires a new block of tasks for execution whenever it becomes idle. To get the best performance, the block size must be chosen to balance the scheduling overhead against the load im balance. To determine the best block size, better analytical models of self-scheduling are needed. We present an experimental study of self-scheduling on a BBN TC2000, a NUMA machine. Previously published models to predict running time and optimal block size were tested using our experimental results. Although the models gave good predictions for small block sizes, for large block sizes the models fail, underestimating the running time by almost a factor of two. We present an upper bound on the running time and use it to explain this failure.