Title

Energy-Aware Adaptive Restore Schemes For Mlc Stt-Ram Cache

Keywords

Multi-level Cell; read disturbance; read reuse distance prediction; STT-RAM; write disturbance

Abstract

For the sake of higher cell density while achieving near-zero standby power, recent research progress in Magnetic Tunneling Junction (MTJ) devices has leveraged Multi-Level Cell (MLC) configurations of Spin-Transfer Torque Random Access Memory (STT-RAM). However, in order to mitigate the write disturbance in an MLC strategy, data stored in the soft bit must be restored back immediately after the hard bit switching is completed. Furthermore, as the result of MTJ feature size scaling, the soft bit can be expected to become disturbed by the read sensing current, thus requiring an immediate restore operation to ensure the data reliability. In this paper, we design and analyze a novel Adaptive Restore Scheme for Write Disturbance (ARS-WD) and Read Disturbance (ARS-RD), respectively. ARS-WD alleviates restoration overhead by intentionally overwriting soft bit lines which are less likely to be read. ARS-RD, on the other hand, aggregates the potential writes and restore the soft bit line at the time of its eviction from higher level cache. Both of these two schemes are based on a lightweight forecasting approach for the future read behavior of the cache block. Our experimental results show substantial reduction in soft bit line restore operations, delivering 17.9 percent decrease in overall energy consumption and 9.4 percent increase in IPC, while incurring negligible capacity overhead. Moreover, ARS promotes advantages of MLC to provide a preferable L2 design alternative in terms of energy, area and latency product compared to SLC STT-RAM alternatives.

Publication Date

5-1-2017

Publication Title

IEEE Transactions on Computers

Volume

66

Issue

5

Number of Pages

786-798

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/TC.2016.2625245

Socpus ID

85018465655 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85018465655

This document is currently not available here.

Share

COinS