Hybrid VC-MTJ/CMOS non-volatile stochastic logic for efficient computing

Wang, Shaodi; Pal, Saptadeep; Li, Tianmu; Pan, Alan; Grèzes, Cécile; Amiri, Pedram Khalili; Wang, Kang L.; Gupta, Puneet

doi:10.23919/date.2017.7927218

Cited by 12 publications

(11 citation statements)

References 23 publications

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“…Furthermore, they have not considered the correlation between different SBGs which will significantly degrade the computation accuracy. Voltage-controlled MTJs (VC-MTJs) are introduced for stochastic computing to reduce the power consumption in [14] but each SBG involves too many MTJs. Bitstream correlation is discussed in [14], however, the proposed shuffle operation could not remove the relevance essentially and may still result in unexpected results.…”

Section: B Magnetic Tunnel Junction (Mtj) Devicementioning

confidence: 99%

SPINBIS: Spintronics-Based Bayesian Inference System With Stochastic Computing

Jia

Yang

Dai

et al. 2020

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Bayesian inference is an effective approach for solving statistical learning problems, especially with uncertainty and incompleteness. However, Bayesian inference is a computingintensive task whose efficiency is physically limited by the bottlenecks of conventional computing platforms. In this work, a spintronics based stochastic computing approach is proposed for efficient Bayesian inference. The inherent stochastic switching behaviors of spintronic devices are exploited to build stochastic bitstream generator (SBG) for stochastic computing with hybrid CMOS/MTJ circuits design. Aiming to improve the inference efficiency, an SBG sharing strategy is leveraged to reduce the required SBG array scale by integrating a switch network between SBG array and stochastic computing logic. A deviceto-architecture level framework is proposed to evaluate the performance of spintronics based Bayesian inference system (SPINBIS). Experimental results on data fusion applications have shown that SPINBIS could improve the energy efficiency about 12× than MTJ-based approach with 45% design area overhead and about 26× than FPGA-based approach.

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Section: B Magnetic Tunnel Junction (Mtj) Devicementioning

confidence: 99%

SPINBIS: Spintronics-Based Bayesian Inference System With Stochastic Computing

Jia

Yang

Dai

et al. 2020

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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“…The MTJ switching mechanism has been demonstrated to be intrinsically stochastic, which has been validated by experimental work [40][41][42]. On the other hand, due to the limited fabrication precision, the development of submicron CMOS transistors and nanometer-level MTJ devices suffer from parametric process variations.…”

Section: Process Variationmentioning

confidence: 81%

“…Based on MTJ theoretical models and several experimental measurements [40][41][42], the MTJ switching procedure can be realized as a stochastic progress because of the thermal fluctuations of magnetization. MTJ switching latency is not deterministic but follows a statistical range.…”

Section: Stochastic Effectsmentioning

confidence: 99%

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High Performance MRAM with Spin-Transfer-Torque and Voltage-Controlled Magnetic Anisotropy Effects

Cai

Wang²,

Wang

et al. 2017

Applied Sciences

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Featured Application: Non-volatile magnetic tunnel junction-based magnetoresistive random access memory as reliable, high energy efficiency Internet of Things (IoTs) node memory.Abstract: The Internet of Things (IoTs) relies on efficient node memories to process data among sensors, cloud and RF front-end. Both mainstream and emerging memories have been developed to achieve this energy efficiency target. Spin transfer torque magnetic tunnel junction (STT-MTJ)-based nonvolatile memory (NVM) has demonstrated great performance in terms of zero standby power, switching power efficiency, infinite endurance and high density. However, it still has a big performance gap; e.g., high dynamic write energy, large latency, yield and reliability. Recently, voltage-controlled magnetic anisotropy (VCMA) has been introduced to achieve improved energy-delay efficiency and robust non-volatile writing control with an electric field or a switching voltage. VCMA-MTJ-based MRAM could be a promising candidate in IoT node memory for high-performance, ultra-low power consumption targets.

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“…STT-MRAM is designed with STT magnetic tunnel junctions (STT-MTJ) [1,2], providing high endurance, fast programming and accessing time, and being identified as a possible replacement of current memory technologies, such as static RAM (SRAM) cache [3,4] and Dynamic RAM (DRAM) memory [5]. MeRAM designed with voltage-control MTJ (VC-MTJ) [6][7][8][9] are switched by voltage-controlled magnetic anisotropy (VCMA) effect, providing more promising programming speed, lower programming energy and higher memory density [10,11].…”

Section: Introductionmentioning

confidence: 99%

Adaptive MRAM Write and Read with MTJ Variation Monitor

Wang

Lee

Grèzes

et al. 2021

IEEE Trans. Emerg. Topics Comput.

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Temperature and wafer-level process variations significantly degrade operation efficiency of Spin-transfer torque random access memory (STT-MRAM) and magnetoelectric random access memory (MeRAM), where the write and read reliability issues are exacerbated by the variations. We propose adaptive write and read schemes for highly efficient STT-MRAM and MeRAM programming and sensing that optimally selects write and read pulses to overcome process and temperature variation. With adaptive write, the write latency of STT-MRAM and MeRAM cache are reduced by up to 17% and 59% respectively, and application run time is improved by up to 41%. With adaptive read, the sensing margin is dramatically improved by 1.4X while maintaining read disturbance correctable by error-correcting-code (ECC) correction. To further mitigate read disturbance impact on memory system, additional adaptive read scheme can dynamically lower read voltage according to the proposed monitor result. It can extend memory service time by haft to one year, and reduce read disturbance induced memory failure by 59% to 84%. To better support these schemes, we also propose, design, and evaluate low-cost MTJ-based variation monitor, which precisely senses process and temperature variation. The monitor is over 10X faster, 5X more energy-efficient, and 20X smaller compared with conventional thermal monitors of similar accuracy.

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Hybrid VC-MTJ/CMOS non-volatile stochastic logic for efficient computing

Cited by 12 publications

References 23 publications

SPINBIS: Spintronics-Based Bayesian Inference System With Stochastic Computing

SPINBIS: Spintronics-Based Bayesian Inference System With Stochastic Computing

High Performance MRAM with Spin-Transfer-Torque and Voltage-Controlled Magnetic Anisotropy Effects

Adaptive MRAM Write and Read with MTJ Variation Monitor

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