A paper is accepted in VLDB 2021: Understanding the Idiosyncrasies of Real Persistent Memory.
Congratulations, Shashank and Arjun!
[VLDB'21] Understanding the Idiosyncrasies of Real Persistent Memory
Shashank Gugnani, Arjun Kashyap, and Xiaoyi Lu.
In Proceedings of the VLDB Endowment, the 47th International Conference on Very Large Data Bases (VLDB) 2021.
High capacity persistent memory (PMEM) is finally commercially available in the form of Intel’s Optane DC Persistent Memory Module (DCPMM). Researchers have raced to evaluate and understand the performance of DCPMM itself as well as systems and applications designed to leverage PMEM resulting from over a decade of research. Early evaluations of DCPMM show that its behavior is more nuanced and idiosyncratic than previously thought. Several assumptions made about its performance that guided the design of PMEM-enabled systems have been shown to be incorrect. Unfortunately, several peculiar performance characteristics of DCPMM are related to the memory technology (3D-XPoint) used and its internal architecture. It is expected that other technologies (such as STT-RAM, memristor, ReRAM, NVDIMM), with highly variable characteristics, will be commercially shipped as PMEM in the near future. Current evaluation studies fail to understand and categorize the idiosyncratic behavior of PMEM; i.e., how do the peculiarities of DCPMM related to other classes of PMEM. Clearly, there is a need for a study which can guide the design of systems and is agnostic to PMEM technology and internal architecture.
In this paper, we first list and categorize the idiosyncratic behavior of PMEM by performing targeted experiments with our proposed PMIdioBench benchmark suite on a real DCPMM platform. Next, we conduct detailed studies to guide the design of storage systems, considering generic PMEM characteristics. The first study guides data placement on NUMA systems with PMEM while the second study guides the design of lock-free data structures, for both eADR- and ADR-enabled PMEM systems. Our results are often counter-intuitive and highlight the challenges of system design with PMEM.