Molecular dynamics (MD) simulations have transformed our understanding of the nanoscale, driving breakthroughs in materials science, computational chemistry, and several other fields, including biophysics and drug design. Even on exascale supercomputers, however, runtimes are excessive for systems and timescales of scientific interest. Here, we demonstrate strong scaling of MD simulations on the Cerebras Wafer-Scale Engine. By dedicating a processor core for each simulated atom, we demonstrate a 179-fold improvement in timesteps per second versus the Frontier GPU-based Exascale platform, along with a large improvement in timesteps per unit energy. Reducing every year of runtime to two days unlocks currently inaccessible timescales of slow microstructure transformation processes that are critical for understanding material behavior and function. Our dataflow algorithm runs Embedded Atom Method (EAM) simulations at rates over 270,000 timesteps per second for problems with up to 800k atoms. This demonstrated performance is unprecedented for general-purpose processing cores.

翻译：分子动力学（MD）模拟深刻改变了我们对纳米尺度的理解，推动了材料科学、计算化学以及生物物理和药物设计等多个领域的突破。然而，即使在百亿亿次超级计算机上，针对具有科学意义的系统和时间尺度的模拟运行时间仍过于冗长。本研究展示了在Cerebras晶圆级引擎上实现MD模拟的强可扩展性。通过为每个模拟原子分配一个处理器核心，我们实现了每秒钟时间步数相比基于GPU的Frontier百亿亿次平台179倍的提升，同时单位能量时间步数也大幅改进。将每年运行时压缩至两天，解锁了目前难以触及的慢速微结构转变过程的时间尺度，这些过程对理解材料行为和功能至关重要。我们的数据流算法可在最多包含80万个原子的算例中，以超过每秒27万步的速率运行嵌入原子法（EAM）模拟。这一性能表现在通用处理核心上史无前例。