Dynamically Reconfigurable Memory Address Mapping for General-Purpose Graphics Processing Unit

Abstract

GPGPUs utilize multi-dimensional memory subsystems to provide the bandwidth needed by their multi-dimensional parallelism. However, an unfavorable address mapping leads to imbalanced memory request distribution across the memory resources, causing degraded performance and poor power efficiency. The optimal mapping is both application- and hardware-dependent. This paper provides a software-hardware co-design to dynamically reconfigure the address mapping according to the trace of the targeted application. First, a circuit to sample the entropy of address bits is proposed to capture the optimal address mapping. Second, a dynamic reconfiguration mechanism is designed to apply the optimal address mapping. Simulation results show up to 45% performance improvement over fixed address mappings.