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Large-memory applications like data analytics and graph processing benefit from extended memory hierarchies, and hybrid DRAM/NVM (non-volatile memory) systems represent an attractive means by which to increase capacity at reasonable performance/energy tradeoffs. Compared to DRAM, NVMs generally have longer latencies and higher energies for writes, which makes careful data placement essential for efficient system operation. Data placement strategies that resort to monitoring all data accesses and migrating objects to dynamically adjust data locations incur high monitoring overhead and unnecessary memory copies due to mispredicted migrations. We find that program semantics (specifically, global access characteristics) can effectively guide initial data placement with respect to memory types, which, in turn, makes run-time migration more efficient. We study a combined offline/online placement …