Reducing server data traffic using a hierarchical computation model

Commercial workloads impose heavy demands on memory and storage subsystems in a server and often result in a large amount of traffic in I/O and memory buses. To reduce the data movement between the storage subsystem and the processing units, we propose a hierarchical computing (HC) system that distributes processing elements across the storage hierarchy. We present a programming model that allows us to decompose database queries into simple operations. These operations are then distributed and executed by the different layers of the hierarchy depending on the affinity of the task to a particular layer. Commands percolate down into the lower layers of the hierarchy and partially processed information flows up into the higher layers, where subsequent operations can be performed. We evaluate the effectiveness of the proposed hierarchical computing model by performing full system simulations of a business decision support system (DSS) workload. On a group of TPC-H-like queries, hierarchical computing systems reduce the amount of data transferred over the processor to memory interconnect by 37-58 percent. We also observe that HC configurations show speedups between 1.14x and 1.45x when compared with CC-NUMA with 32 processors.