Abstract

This article presents an on-line scheduling algorithm that is provably space e#cient and time e#cient for nested-parallel languages. For a computation with depth D and serial space requirement S1 , the algorithm generates a schedule that requires at most S1 +O(K D p)space (including scheduler space) on p processors. Here, K is a user-adjustable runtime parameter specifying the net amount of memory that a thread may allocate before it is preempted by the scheduler. Adjusting the value of K provides a trade-o# between the running time and the memory requirement of a parallel computation. To allow the scheduler to scale with the number of processors, we also parallelize the scheduler and analyze the space and time bounds of the computation to include scheduling costs. In addition to showing that the scheduling algorithm is space and time e#cient in theory, we demonstrate that it is e#ective in practice. We have implemented a runtime system that uses our algorithm to schedule lightweight parallel threads. The results of executing parallel programs on this system show that our scheduling algorithm significantly reduces memory usage compared to previous techniques, without compromising performance

Citations