Computer Science ›› 2018, Vol. 45 ›› Issue (6A): 562-567.

• Interdiscipline & Application • Previous Articles     Next Articles

Optimization of Register Allocation Strategy for MLC STT-RAM

NI Yuan-hui1,CHEN Wei-wen1,WANG Lei1,QIU Ke-ni1,2   

  1. College of Information Engineering,Capital Normal University,Beijing 100048,China1
    Beijing Advanced Innovation Center for Imaging Technology,Beijing 100048,China2
  • Online:2018-06-20 Published:2018-08-03

Abstract: Multi-level cell spin-transfer torque random access memory (MLC STT-RAM) is a promising nonvolatile memory technology.Unlike the SRAM that uses a charge mode to store information,MLC STT-RAM uses the spin polarization current to change the magnetic layer direction of the free layer through the magnetic tunneling junction (MTJ) to store information,so it can naturally avoid electromagnetic interference.This paper used the anti-electromagnetic radiation characteristics of MLC STT-RAM,and explored it as a register for its natural immunity to electromagnetic radiation in rad-hard space environment.MLC STT-RAM exhibits unbalanced write-state transitions due to the fact that the magnetization directions of hard and soft domains cannot be flipped.This feature leads to nonuniform costs of write-states in terms of latency and energy.However,current SRAM-targeting register allocations do not have a clear understanding of the impact of the different write-state transition costs.As a result,those approaches heuristically select variables to be spilled without considering the spilling priority imposed by MLC STT-RAM.Aiming to address this li-mitation,this paper proposed a state-transition aware spilling cost minimization (SSCM) policy to save power when MLC STT-RAM is employed in register design.Specifically,the spilling cost model is first constructed according to the linear combination of different state transition frequencies.Directed by the proposed cost model,the compiler picks up spilling candidates with the highest cost to achieve lower power and higher performance.

Key words: MLC STT-RAM, Write-state transition, Potential spilling, Register allocation

CLC Number: 

  • TP336
[1]LIANG S,CHUN X,HU J,et al.Write activity reduction on flash main memory via smart victim cache[C]∥Great Lakes Symposium on VLSI Systems.2010:91-94.
[3]CHABI D,ZHAO W S,JACQUES-OLIVIER K,et al.Design and analysis of radiation hardened sensing circuits for spin transfer torque magnetic memory and logic[J].IEEE Transactions on Nuclear Science,2014,61(6):3258-3264.
[4]HUGHES H,BUSSMANN K,MCMARR P al.Radiation studies of spin-transfer torque materials and devices[J].IEEE Transactions on Nuclear Science,2012,59 (6):3027-3033.
[5]BISHNOI R,EBRAHIMI M,OBORIL F,et al.Improving write performance for STT-MRAM[J].IEEE Transactions on Magnetics,2016,52(8):1-11.
[9]CHEN Y R,WANG X B,ZHU W Z,et al.Access scheme of multi-level cell spin-transfer torque random access memory and its optimization[C]∥Midwest Symposium on Circuits and Systems.2010:1109-1112.
[11]CHAITIN,AUSLANDER,CHANDRA,et al.P.W.:Register allocation via graph coloring[J].Journal of Computer Languages,1981,238(16):265-266.
[12]COOPER K,DASGUPTA A,et al.Tailoring graph-coloring register allocation for runtime compilation[C]∥Code Generation and Optimization.2006:39-49.
[16]FALK H.WCET-aware register allocation based on graph coloring[C]∥Design Automation Conference.2009:726-731.
[17]LOU X H,GAO Z,DIMITORV,et al.Demonstration of multilevel cell spin transfer switching in mgo magnetic tunnel junctions[J].Applied Physics Letters,2008,93(24):242-502.
[18]ZHAO M Y,XUE Y,YANG C M,et al.Minimizing MLC PCM write energy for free through profiling-based state remapping[C]∥Asia and South Pacific Design Automation Conference.2015:502-507.
[19]ZHAO M Y,XUE Y,HU J T,et al.State asymmetry driven state remapping in phase change memory[J].IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems,2016,36(1):27-40.
[20]LIU X X,MAO M J,BI X Y,et al.An efficient stt-ram-based register file in gpu architectures[C]∥Asia and South Pacific Design Automation Conference.2015:490-495.
[21]LATTNER C,ADVE V.LLVM:A compilation framework for lifelong program analysis & transformation[C]∥Code Generation and Optimization.2004:75-86.
[22]LUO H Z,HU J T,SHI L,et al.Two-step state transition minimization for lifetime and performance improvement on MLC STT-RAM[C]∥Design Automation Conference.2016:1-6.
[1] QIU Ya-qiong, HU Yong-hua, LI Yang, TANG Zhen, SHI Lin. Optimization Algorithm of Complementary Register Usage Between Two Register Classesin Register Spilling for DSP Register Allocation [J]. Computer Science, 2019, 46(6): 196-200.
[2] WU Sheng-Ning, LI Si-Kun (School of Computer Science, National University of Defense Technology, Changsha 410073). [J]. Computer Science, 2007, 34(8): 278-280.
Full text



[1] . [J]. Computer Science, 2018, 1(1): 1 .
[2] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[3] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[4] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[5] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[6] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[7] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[8] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[9] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[10] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .