University of Oregon Eugene, United States of America
Due to increasing complexity in the memory hierarchy, predicting the performance of a given application in a given processor is becoming more difficult. The problem is worsened by the fact that the hardware needed to deal with more complex memory traffic also affects energy consumption. Moreover, in a heterogeneous system with shared main memory, the memory traffic between the last level cache (LLC) and the memory creates contention between other processors and accelerator devices. For these reasons, it is important to investigate and understand the impact of different memory access patterns on the memory system.
This study investigates the interplay between Intel processors' memory hierarchy and different memory access patterns in applications. The authors explore streaming and strided memory access patterns with the objective of predicting LLC-DRAM traffic for a given application in given Intel architectures. Moreover, the impact of prefetching is also investigated in this study. Experiments with different Intel micro-architectures uncover mechanisms to predict LLC-DRAM traffic that can yield up to 99% accuracy for streaming access patterns and up to 95% accuracy for strided access patterns.