Investigating bio-inspired architectures for efficient computation

经典的数字计算耗电、脆弱，而且很难与模拟的真实世界对接。非传统计算机，如材料储存库计算机(RCS)，可以帮助克服这些问题，特别是通过执行能够直接利用其材料组成的自然动力学的具体化计算，从而显著降低功率需求。这样的设备原则上已经得到了证明，但系统需要扩大规模，才能为现实世界的任务提供足够和适当的计算能力。此外，需要一系列设备配置来支持不同的计算任务。我们的目标是开发用于组合多个材料RC的技术：1.使用相似的实例配置，以提供可扩展性2.使用不同的实例配置，以共同执行任何单个RC配置都不能单独执行的任务。

Classical digital computing is power-hungry, fragile, and hard to interface to the analogue real world. Unconventional computers such as in materio Reservoir Computers (RCs) can help overcome these issues, particularly by being able to perform embodied computation that can directly exploit the natural dynamics of their material composition, thereby dramatically reducing the power requirements. Such devices have been proven in principle, but systems need to be scaled up to provide sufficient and appropriate computational power for real-world tasks. Furthermore, a range of device configurations is needed to support different computational tasks. Our aim is to develop techniques for combining multiple material RCs: 1. with similar instance configurations, to provide scalability 2. with diverse instance configurations, to perform together tasks that no single RC configuration can readily perform alone.