Load Balancing Performance of Dynamic Scheduling on NUMA Multiprocessors

Self scheduling is a method for task scheduling 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 imbalance To determine the best block size a better understanding of the role of load imbalance in self scheduling performance is needed In this paper we study the e ect of memory contention on task duration distributions and hence load balancing in self scheduling on a Non Uniform Memory Access NUMA machine Experimental studies on a BBN TC are used to reveal the strengths and weaknesses of analytical performance models to predict running time and optimal block size The models are shown to be very accurate for small block sizes However the models fail when the block size is large due to a previously unrecognized source of load imbalance We extend the analytical models to address this failure The implications for the construction of compilers and runtime systems are discussed