Feedback-directed pipeline parallelism

Abstract

Extracting high performance from Chip Multiprocessors requires that the application be parallelized. A common software technique to parallelize loops is pipeline parallelism in which the programmer/compiler splits each loop iteration into stages and each stage runs on a certain number of cores. It is important to choose the number of cores for each stage carefully because the core-to-stage allocation determines performance and power consumption. Finding the best core-to-stage allocation for an application is challenging because the number of possible allocations is large, and the best allocation depends on the input set and machine configuration. This paper proposes Feedback-Directed Pipelining (FDP), a software framework that chooses the core-to-stage allocation at run-time. FDP first maximizes the performance of the workload and then saves power by reducing the number of active cores, without impacting performance. Our evaluation on a real SMP system with two Core2Quad processors (8 cores) shows that FDP provides an average speedup of 4.2x which is significantly higher than the 2.3x speedup obtained with a practical profile-based allocation. We also show that FDP is robust to changes in machine configuration and input set.