MemPod: A Clustered Architecture for Efficient and Scalable Migration in Flat Address Space Multi-level Memories

In the near future, die-stacked DRAM will be increasingly present in conjunction with off-chip memories in hybrid memory systems. Research on this subject revolves around using the stacked memory as a cache or as part of a flat address space. This paper proposes MemPod, a scalable and efficient memory management mechanism for flat address space hybrid memories. MemPod monitors memory activity and periodically migrates the most frequently accessed memory pages to the faster on-chip memory. MemPod's partitioned architectural organization allows for efficientscaling with memory system capabilities. Further, a big data analytics algorithm is adapted to develop an efficient, low-cost activity tracking technique. MemPod improves the average main memory access time of multi-programmed workloads, by up to 29% (9% on average) compared to the state of the art, and that will increase as the differential between memory speeds widens. MemPod's novel activity tracking approach leads to significant cost reduction (12800x lower storage space requirements) and improved future prediction accuracy over prior work which maintains a separatecounter per page.