A Case for Efficient Hardware/Software Cooperative Management of Storage and Memory

Fifth Workshop on Energy-Efficient Design (WEED 2013). Held in conjunction with the 2013 International Symposium on Computer Architecture (ISCA-40). June 24, 2013, Tel-Aviv, Israel.

Justin Meza*, Yixin Luo*, Samira Khan*‡, Jishen Zhao†, Yuan Xie†§, Onur Mutlu*

*Carnegie Mellon University
5000 Forbes Ave.
Pittsburgh, PA 15213

†Pennsylvania State University
‡Intel Labs
§AMD Research


Most applications manipulate persistent data, yet traditional systems decouple data manipulation from persistence in a two-level storage model. Programming languages and system software manipulate data in one set of formats in volatile main memory (DRAM) using a load/store interface, while storage systems maintain persistence in another set of formats in non-volatile memories, such as Flash and hard disk drives in traditional systems, using a file system interface. Unfortunately, such an approach suffers from the system performance and energy overheads of locating data, moving data, and translating data between the different formats of these two levels of storage that are accessed via two vastly different interfaces.

Yet today, new non-volatile memory (NVM) technologies show the promise of storage capacity and endurance similar to or better than Flash at latencies comparable to DRAM, making them prime candidates for providing applications a persistent single-level store with a single load/store interface to access all system data. Our key insight is that in future systems equipped with NVM, the energy consumed executing operating system and file system code to access persistent data in traditional systems becomes an increasingly large contributor to total energy. The goal of this work is to explore the design of a Persistent Memory Manager that coordinates the management of memory and storage under a single hardware unit in a single address space. Our initial simulation-based exploration shows that such a system with a persistent memory can improve energy efficiency and performance by eliminating the instructions and data movement traditionally used to perform I/O operations.





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