Antiferromagnetic Tunnel Junctions (AFMTJs) for In-Memory Computing: Modeling and Case Study
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866914315479547904 |
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| author | Choudhary, Yousuf Adegbija, Tosiron |
| author_facet | Choudhary, Yousuf Adegbija, Tosiron |
| contents | Antiferromagnetic Tunnel Junctions (AFMTJs) enable picosecond switching and femtojoule writes through ultrafast sublattice dynamics. We present the first end-to-end AFMTJ simulation framework integrating multi-sublattice Landau-Lifshitz-Gilbert (LLG) dynamics with circuit-level modeling. SPICE-based simulations show that AFMTJs achieve ~8x lower write latency and ~9x lower write energy than conventional MTJs. When integrated into an in-memory computing architecture, AFMTJs deliver 17.5x average speedup and nearly 20x energy savings versus a CPU baseline-significantly outperforming MTJ-based IMC. These results establish AFMTJs as a compelling primitive for scalable, low-power computing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_08323 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Antiferromagnetic Tunnel Junctions (AFMTJs) for In-Memory Computing: Modeling and Case Study Choudhary, Yousuf Adegbija, Tosiron Hardware Architecture Emerging Technologies Antiferromagnetic Tunnel Junctions (AFMTJs) enable picosecond switching and femtojoule writes through ultrafast sublattice dynamics. We present the first end-to-end AFMTJ simulation framework integrating multi-sublattice Landau-Lifshitz-Gilbert (LLG) dynamics with circuit-level modeling. SPICE-based simulations show that AFMTJs achieve ~8x lower write latency and ~9x lower write energy than conventional MTJs. When integrated into an in-memory computing architecture, AFMTJs deliver 17.5x average speedup and nearly 20x energy savings versus a CPU baseline-significantly outperforming MTJ-based IMC. These results establish AFMTJs as a compelling primitive for scalable, low-power computing. |
| title | Antiferromagnetic Tunnel Junctions (AFMTJs) for In-Memory Computing: Modeling and Case Study |
| topic | Hardware Architecture Emerging Technologies |
| url | https://arxiv.org/abs/2602.08323 |