DocumentCode :
3676015
Title :
Exploring data placement in racetrack memory based scratchpad memory
Author :
Haiyu Mao;Chao Zhang;Guangyu Sun;Jiwu Shu
Author_Institution :
Department of Computer Science and Technology, Tsinghua University, China
fYear :
2015
fDate :
8/1/2015 12:00:00 AM
Firstpage :
1
Lastpage :
5
Abstract :
Scratchpad Memory (SPM) has been widely adopted in various computing systems to improve performance of data access. Recently, non-volatile memory technologies (NVMs) have been employed for SPM design to improve its capacity and reduce its energy consumption. In this paper, we explore data allocation in SPM based on racetrack memory (RM), which is an emerging NVM with ultra-high storage density and fast access speed. Since a shift operation is needed to access data in RM, data allocation has an impact on performance of RM based SPM. Several allocation methods have been discussed and compared in this work. Especially, we addressed how to leverage genetic algorithm to achieve near-optimal data allocation.
Keywords :
"Genetic algorithms","Resource management","Nonvolatile memory","Biological cells","Yttrium","Random access memory","Sun"
Publisher :
ieee
Conference_Titel :
Non-Volatile Memory System and Applications Symposium (NVMSA), 2015 IEEE
Type :
conf
DOI :
10.1109/NVMSA.2015.7304358
Filename :
7304358
Link To Document :
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