Intel Optane DC persistent memory module (DCPMM) is an emergent non-volatile memory (NVM) technology that is promising due to its byte-addressability, high density, and similar performance to DRAM. Prior literature explores a new architectural paradigm, coined hybrid memory architecture (HMA), which results of the configuration of NVM as a memory tier between DRAM and storage. HMAs have the potential to improve applications by enabling them to place a larger working set in fast memory, and thus reduce the need of evicting data to slow block-based storage. HMAs also mitigate the well-known memory scalability problem, common in a plethora of large servers and supercomputers. These systems cannot deploy more physical memory due to size, energy or cost limitations, all of which are alleviated by NVM integration. However, most NVM research explores its non-volatility as an enabler to faster data persistence, neglecting the scalability benefit offered by NVM integration, in the HMA scenario. Conversely, existing NVM research in the data placement field precedes the commercial availability of NVM, testing HMAs in often-inaccurate simulation-based environments, inferring NVM’s performance from outdated technologies. Our thesis proposes Ambix, the first published solution tested on a real system running DCPMM, which decides page placement dynamically in a Linux system. We extensively discuss how different memory policies and distributions affect throughput and energy consumption in a DRAM-DCPMM system, leveraging the conclusions to guide Ambix ’s design. We show that Ambix has an up to 10x speedup in HPC-dedicated benchmarks, compared to the default memory policy in Linux.
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