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Proceedings/Recueil Des Communications Année : 2021

Cryogenic In-MRAM Computing

Résumé

In the computation storage separated von-Neumann architecture, memory-wall becomes critical due to large access latency and tremendous amount of data movement. In this work, we pursue cryogenic temperature based memory design and focus on spin-transfer-torque magnetoresistive random access memory (STT-MRAM) at 77-Kelvin (achieved with low-cost liquid nitrogen). Cryogenic compact model and related cryogenic bitcell are investigated based on 77K experiment data of magnetic tunnel junction (MTJ) and CMOS transistor. Aggressive energy reduction is obtained through in-MRAM computing architecture. A 1Kb sub-array is simulated based on above cryogenic models. Results show that cryogenic in-MRAM computing provides performance improvements of 32% on average, and concurrently reduces memory energy consumption by 19% on average. Compared with room temperature (RT) simulation results, a 70% reduction of sensing latency is realized at 0.7-V supply voltage, with the cost of 30% increased writing latency and 20% higher energy consumption. A 32.5% sensing failure probability is alleviated in the 77K cryogenic environment. The proposed 77K cryogenic design methodology can be further applied to energy constrained applications.
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Dates et versions

hal-04420929 , version 1 (27-01-2024)

Identifiants

Citer

Yaoru Hou, We Ge, Yanan Guo, Lirida Naviner, You Wang, et al.. Cryogenic In-MRAM Computing. 2021 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH), IEEE, pp.1-6, 2021, ⟨10.1109/NANOARCH53687.2021.9642238⟩. ⟨hal-04420929⟩
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