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Kai Wu, Dong Li. Unimem: Runtime Data Management on Non-Volatile Memory-Based Heterogeneous Main Memory for High Performance Computing[J]. Journal of Computer Science and Technology, 2021, 36(1): 90-109. DOI: 10.1007/s11390-020-0942-z
Citation: Kai Wu, Dong Li. Unimem: Runtime Data Management on Non-Volatile Memory-Based Heterogeneous Main Memory for High Performance Computing[J]. Journal of Computer Science and Technology, 2021, 36(1): 90-109. DOI: 10.1007/s11390-020-0942-z

Unimem: Runtime Data Management on Non-Volatile Memory-Based Heterogeneous Main Memory for High Performance Computing

  • Non-volatile memory (NVM) provides a scalable and power-efficient solution to replace dynamic random access memory (DRAM) as main memory. However, because of the relatively high latency and low bandwidth of NVM, NVM is often paired with DRAM to build a heterogeneous memory system (HMS). As a result, data objects of the application must be carefully placed to NVM and DRAM for the best performance. In this paper, we introduce a lightweight runtime solution that automatically and transparently manages data placement on HMS without the requirement of hardware modifications and disruptive change to applications. Leveraging online profiling and performance models, the runtime solution characterizes memory access patterns associated with data objects, and minimizes unnecessary data movement. Our runtime solution effectively bridges the performance gap between NVM and DRAM. We demonstrate that using NVM to replace the majority of DRAM can be a feasible solution for future HPC systems with the assistance of a software-based data management.
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