Abstract: Processing-in-memory (PIM) is an emerging technology to alleviate the high cost of data movement by pushing computation into/near memory modules. There is an inherent tension, however, between minimizing communication (data movement) and achieving load balance in PIM systems in the presence of workload skew. This work introduces PIM-tree, a PIM-based index that simultaneously achieves low communication, good load balance, and low space consumption. It achieves good theoretical bounds in the PIM Model and efficient on a real-world PIM machine, outperforming prior PIM-based and state-of-the-art CPU-based indexes.
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