An Empirical Guide to the Behavior and Use of Scalable Persistent Memory

Authors: 

Jian Yang, Juno Kim, and Morteza Hoseinzadeh, UC San Diego; Joseph Izraelevitz, University of Colorado, Boulder; Steve Swanson, UC San Diego

Abstract: 

After nearly a decade of anticipation, scalable nonvolatile memory DIMMs are finally commercially available with the release of Intel’s Optane DIMM. This new nonvolatile DIMM supports byte-granularity accesses with access times on the order of DRAM, while also providing data storage that survives power outages.

Researchers have not idly waited for real nonvolatile DIMMs (NVDIMMs) to arrive. Over the past decade, they have written a slew of papers proposing new programming models, file systems, libraries, and applications built to exploit the performance and flexibility that NVDIMMs promised to deliver. Those papers drew conclusions and made design decisions without detailed knowledge of how real NVDIMMs would behave or how industry would integrate them into computer architectures. Now that Optane NVDIMMs are actually here, we can provide detailed performance numbers, concrete guidance for programmers on these systems, reevaluate prior art for performance, and reoptimize persistent memory software for the real Optane DIMM.

In this paper, we explore the performance properties and characteristics of Intel’s new Optane DIMM at the micro and macro level. First, we investigate the basic characteristics of the device, taking special note of the particular ways in which its performance is peculiar relative to traditional DRAM or other past methods used to emulate NVM. From these observations, we recommend a set of best practices to maximize the performance of the device. With our improved understanding, we then explore and reoptimize the performance of prior art in application-level software for persistent memory.

FAST '20 Open Access Sponsored by NetApp

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BibTeX
@inproceedings {246192,
author = {Jian Yang and Juno Kim and Morteza Hoseinzadeh and Joseph Izraelevitz and Steve Swanson},
title = {An Empirical Guide to the Behavior and Use of Scalable Persistent Memory},
booktitle = {18th {USENIX} Conference on File and Storage Technologies ({FAST} 20)},
year = {2020},
isbn = {978-1-939133-12-0},
address = {Santa Clara, CA},
pages = {169--182},
url = {https://www.usenix.org/conference/fast20/presentation/yang},
publisher = {{USENIX} Association},
month = feb,
}

Presentation Video