@inproceedings{narayanan2019getting,
author = {Narayanan, Iyswarya and Ganesan, Aishwarya and Badam, Anirudh and Govindan, Sriram and Sharma, Bikash and Sivasubramaniam, Anand},
title = {Getting More Performance with Polymorphism from Emerging Memory Technologies},
booktitle = {International Systems and Storage Conference (SYSTOR)},
year = {2019},
month = {April},
abstract = {Storage-intensive systems in data centers rely heavily on DRAM and SSDs for the performance of reads and persistent writes, respectively. These applications pose a diverse set of requirements, and are limited by fixed capacity, fixed access latency, and fixed function of these resources as either memory or storage. In contrast, emerging memory technologies like 3D-Xpoint, battery-backed DRAM, and ASIC-based fast memory-compression offer capabilities across several dimensions. However, existing proposals to use such technologies can only improve either read or write performance but not both without requiring extensive changes to the application,and the operating system. We present PolyEMT, a system that employs an emerging memory technology based cache to the SSD, and transparently morphs the capabilities of this cache across several dimensions - persistence, capacity, latency - to jointly improve both read and write performance. We demonstrate the benefits of PolyEMT using several large-scale storage-intensive workloads from our data centers.},
publisher = {ACM},
url = {http://approjects.co.za/?big=en-us/research/publication/getting-more-performance-with-polymorphism-from-emerging-memory-technologies/},
}