IBM Research-Zurich, Säumerstrasse 4, 8803, Rüschlikon, Switzerland.
Nat Commun. 2017 Oct 24;8(1):1115. doi: 10.1038/s41467-017-01481-9.
Conventional computers based on the von Neumann architecture perform computation by repeatedly transferring data between their physically separated processing and memory units. As computation becomes increasingly data centric and the scalability limits in terms of performance and power are being reached, alternative computing paradigms with collocated computation and storage are actively being sought. A fascinating such approach is that of computational memory where the physics of nanoscale memory devices are used to perform certain computational tasks within the memory unit in a non-von Neumann manner. We present an experimental demonstration using one million phase change memory devices organized to perform a high-level computational primitive by exploiting the crystallization dynamics. Its result is imprinted in the conductance states of the memory devices. The results of using such a computational memory for processing real-world data sets show that this co-existence of computation and storage at the nanometer scale could enable ultra-dense, low-power, and massively-parallel computing systems.
基于冯·诺依曼架构的传统计算机通过在其物理上分离的处理和存储单元之间反复传输数据来进行计算。随着计算越来越以数据为中心,并且在性能和功率方面达到了可扩展性的限制,人们正在积极寻求具有协同计算和存储的替代计算范例。一种引人入胜的方法是计算内存,其中纳米级存储设备的物理特性被用于在非冯·诺依曼方式下在存储单元内执行某些计算任务。我们通过使用一百万相变存储设备进行了实验演示,这些设备通过利用结晶动力学来执行高级计算基元。其结果被印在存储设备的电导状态中。使用这种计算内存处理真实数据集的结果表明,这种纳米级计算和存储的共存可能会实现超密集、低功耗和大规模并行计算系统。