The Development of In-Memory Data Systems. In

The continuous growth of main memory size allows mod-ern data systems to process entire large scale datasets in memory. The increase in memory capacity, however, is not matched by proportional decrease in memory latency, caus-ing a mismatch for in-memory processing. As a result, data movement through the memory hierarchy is now one of the main performance bottlenecks for main memory data sys-tems. Database systems researchers have proposed several innovative solutions to minimize data movement and to make data access patterns hardware-aware. Nevertheless, all rele-vant rows and columns for a given query have to be moved through the memory hierarchy; hence, movement of large data sets is on the critical path. In this paper, we present JAFAR, a Near-Data Processing (NDP) accelerator for pushing selects down to memory in modern column-stores. JAFAR implements the select oper-ator and allows only qualifying data to travel up the memory hierarchy. Through a detailed simulation of JAFAR hard-ware we show that it has the potential to provide 9 × im-provement for selects in column-stores. In addition, we dis-cuss both hardware and software challenges for using NDP in database systems as well as opportunities for further NDP accelerators to boost additional relational operators