Ameliorating memory contention of OLAP operators on GPU processors
Evangelia A. Sitaridi, Kenneth Andrew Ross · 2012
Implementations of database operators on GPU processors have shown dramatic performance improvement compared to multicore-CPU implementations. GPU threads can cooperate using shared memory, which is organized in interleaved banks and is fast only when threads read and modify addresses belonging to distinct memory banks. Therefore, data processing operators implemented on a GPU, in addition to contention caused by popular values, have to deal with a new performance limiting factor: thread serialization when accessing values belonging to the same bank.