DocumentCode :
3478014
Title :
Stochastic computation with Spin Torque Transfer Magnetic Tunnel Junction
Author :
de Barros Naviner, Lirida Alves ; Hao Cai ; You Wang ; Weisheng Zhao ; Ben Dhia, Arwa
Author_Institution :
Inst. Mines-Telecom, Telecom-ParisTech, Paris, France
fYear :
2015
fDate :
7-10 June 2015
Firstpage :
1
Lastpage :
4
Abstract :
Stochastic Computing (SC) with random bit streams has been used to replace binary radix encoding. SC-based logic circuits take advantage of area minimization, fast and accurate operation and inherent fault tolerance. In this paper, the stochastic characteristics inherent in Spin Torque Transfer Magnetic Tunnel Junction (STT-MTJ) bring on an innovative stochastic number generator (SNM) circuit. The hybrid MOS-MTJ process allows to design a 4T1M structure SNM with 1.98μm*1.46μm layout area, using 28 nm ultra thin body and buried oxide fully depleted silicon-on-insulator (UTBB FD-SOI) technology. A case study of designed SNM is performed by polynomial function synthesis, which significantly reduces area. The proposed circuit also takes advantage of non-volatility and infinite endurance from STT-MTJs, which can be applied to reliability-aware circuits and systems1.
Keywords :
MOS integrated circuits; fault tolerance; logic circuits; magnetic tunnelling; polynomials; silicon-on-insulator; 4T1M structure SNM; SC-based logic circuits; SNM circuit; UTBB FD-SOI technology; area minimization; buried oxide; fault tolerance; fully depleted silicon-on-insulator; hybrid MOS-MTJ process; innovative stochastic number generator circuit; magnetic tunnel junction; polynomial function synthesis; random bit streams; size 28 nm; spin torque transfer; stochastic computation; ultra thin body; Generators; Junctions; Magnetic tunneling; Polynomials; Stochastic processes; Switches; Torque; Approximate Computing; Magnetic Tunnel Junction; Stochastic Number Generator;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
New Circuits and Systems Conference (NEWCAS), 2015 IEEE 13th International
Conference_Location :
Grenoble
Type :
conf
DOI :
10.1109/NEWCAS.2015.7182031
Filename :
7182031
Link To Document :
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