Investigating bio-inspired architectures for efficient computation

研究仿生架构以实现高效计算

• 批准号: 2894696
• 金额: --
• 依托单位: University of Sheffield
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2894696
• 关键词: Investigating; bio; inspired; architectures; efficient

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.

传统的数字计算是耗电的，脆弱的，很难接口到模拟的真实的世界。非传统的计算机，如材料库计算机（RC），可以帮助克服这些问题，特别是通过能够执行嵌入式计算，可以直接利用其材料成分的自然动态，从而大大降低功率需求。这些设备已经在原则上得到了验证，但系统需要扩大规模，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。我们的目标是开发多种材料RC相结合的技术：1。具有类似的实例配置，以提供可伸缩性2.使用不同的实例配置，一起执行单个RC配置无法单独执行的任务。