A new non-blocking approach on GPU dynamical memory management

Abstract

Dynamic memory allocation is a very important and basic technique implemented on modern computer architecture. In the massively parallel processor (MPP) architecture such as Graphics Processing Units (GPUs), many threads try to send allocation or deallocation requests to system in the same time, which could cause the issue of synchronization or race condition. In this paper, we design a new signal model with signal queue to handle the interaction of threads. Based on the signal model, we involve the concept of buddy memory to construct a non-blocking parallel buddy system. Our design have no synchronization problem and adopt a simpler structure implemented than before. Finally, we implement our model in real hardware and experimental results show that the model have better performance than other methods.