03/06/2025, 06:49 AM UTC
硅基神经元：SENNA人工智能芯片加速脉冲神经网络Neurons Cast in Silicon: The SENNA AI Chip Accelerates Spiking Neural Networks
弗劳恩霍夫集成电路研究所IIS开发了一款用于处理脉冲神经网络（SNNs）的人工智能芯片。受大脑功能启发的SENNA脉冲神经网络推理加速器由人工神经元组成，可以直接处理电脉冲（ spikes）。它的速度、能效和紧凑的设计使其能够直接在数据生成的地方使用：边缘设备。
SNNs由通过突触连接的人工神经元网络组成。信息以电脉冲的形式传输和处理，使脉冲网络成为人工智能的下一个步骤：更快、更节能、更接近人脑的处理方式。要将这些优势应用于实际，需要小型、高效的硬件，可以模仿神经元和突触的结构。为此，弗劳恩霍夫IIS在SEC-Learn项目中开发了神经形态SNN加速器SENNA。
SENNA是一种用于AI应用的低维时间序列数据快速处理的神经形态芯片。当前版本由小于11平方毫米的芯片面积上的1024个人工神经元组成。其低至20纳秒的响应时间确保在边缘的时敏应用中精确计时。这使得它在基于事件的实时传感器数据处理和闭环控制系统中特别强大，例如使用AI控制小型电机。在通信系统中，可以使用SENNA实现AI优化的数据传输。在那里，AI处理器可以分析信号流，并根据需要调整传输和接收方法，以提高效率和性能。
The Fraunhofer Institute for Integrated Circuits IIS has developed an AI chip for processing Spiking Neural Networks (SNNs). The SENNA spiking neural network inference accelerator, inspired by brain function, consists of artificial neurons and can process electrical impulses (spikes) directly. Its speed, energy efficiency, and compact design enable the use of SNNs directly where data is generated: in edge devices.
SNNs consist of a network of artificial neurons connected by synapses. Information is transmitted and processed in the form of electrical impulses, allowing pulsing networks to be the next step in artificial intelligence: faster, more energy-efficient, and closer to the processing method of the human brain. To bring these advantages into application, small, efficient hardware that mimics a structure of neurons and synapses is needed. For this, the Fraunhofer IIS has developed the neuromorphic SNN accelerator SENNA as part of the Fraunhofer project SEC-Learn.
SENNA is a neuromorphic chip for fast processing of low-dimensional time series data in AI applications. The current version consists of 1024 artificial neurons on less than 11 mm² of chip area. Its low reaction time down to 20 nanoseconds ensures precise timing in time-critical applications at the edge. This makes it particularly strong in real-time event-based sensor data processing and in closed control systems, such as the control of small electric motors with AI. With SENNA, AI-optimized data transmission can be realized in communication systems. There, the AI processor can analyze signal streams and adjust transmission and reception methods as needed to improve efficiency and performance.
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