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.

翻译：反铁磁隧道结通过超快亚晶格动力学实现皮秒级切换与飞焦耳级写入。我们首次提出端到端的AFMTJ仿真框架，将多亚晶格朗道-利夫希茨-吉尔伯特动力学与电路级建模相结合。基于SPICE的仿真表明，AFMTJ相比传统MTJ可实现约8倍的写入延迟降低与约9倍的写入能耗降低。当集成至存内计算架构时，相较于CPU基准，AFMTJ能带来17.5倍的平均加速与近20倍的节能效果，显著优于基于MTJ的存内计算方案。这些结果确立了AFMTJ作为可扩展低功耗计算核心单元的优越性。