Perspective: an optoelectronic future for heterogeneous, dendritic computing

Area of Science:

• Computer Engineering
• Neuroscience
• Materials Science

Background:

• Growing demand for large neural network models necessitates novel computing architectures.
• Advancements in co-integrated silicon photonics and CMOS circuits offer new possibilities.
• High bandwidth optical networks and high-speed computing are critical for future applications.

Purpose of the Study:

• To discuss current trends in neuromorphic computing architecture.
• To outline a future direction for neuromorphic computing.
• To explore the potential of optoelectronic, heterogeneous, dendritic architectures.

Main Methods:

• Review of current neuromorphic computing trends.
• Analysis of silicon photonic and CMOS integration.
• Conceptualization of optoelectronic dendritic architectures.

Main Results:

• Identification of key trends shaping neuromorphic computing.
• Proposal of an optoelectronic approach for enhanced computing.
• Highlighting the synergy between photonics and CMOS.

Conclusions:

• Heterogeneous, dendritic neuromorphic computing offers a promising path forward.
• Optoelectronic integration is key to achieving high-performance computing for AI.
• Future architectures will leverage optical and electronic components for greater efficiency.