Integrating photonics for accelerated information processing

Integrating photonics for accelerated information processing

Photonics has already played a pivotal role in the internet cables that carry data globally and serve as a fundamental technology for data transmission within data centres.

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Recently, photonics has attracted significant attention for computing applications. The same principles that benefit communication – low latency, energy efficiency, and the capacity to process data on the fly – are now being explored to overcome the limitations of electronic computing (such as energy consumption, latency, and bandwidth). This will benefit applications such as in the acceleration of neural networks, data centre workloads, and edge AI.

Maturity

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Changing dynamics in Responsible AI From large to small language models AR and smart glasses become more prominent Increasing AI-enhanced user experience Growing big tech competition for the XR stack Increased application of FAIR principles to enable digital ecosystems in Europe Growing relevance of TRUST principles for data repositories to secure data More decentralisation of data ownership enabled by SSI solutions Emergence of organisational wallets Push for transparent supply chains with digital product passports Bringing computing resources closer to the ‘edge’ Growing need for automated cloud and edge resource management Growing emphasis on neuromorphic (brain-inspired) computing Integrating photonics for accelerated information processing The battle for airwaves AI/Ops, digital twinning and the emergence of the LLM in network operations Power usage and ecological footprint From ad hoc experiments to applications Towards Fault-Tolerant Quantum Computing (FTQC) Cyber-physical technology calls for resilient minds A growing urge for chip sovereignty in Europe

Public Values

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Drivers

Automation & AI;

Engineering advances & computation;

Energy supply & demand;

Clean water demand;

Critical infrastructure;

Impact

Education

If optical computing continues to mature as a foundational technology for data processing and communication, education will inevitably need to evolve accordingly. The traditional focus on electronic-based computation in engineering curricula will no longer suffice to prepare students for the hybrid electronic and photonic systems of the future. At institutions such as TU Eindhoven, where an elective course on optical computing has already been introduced, this evolution has commenced. While still optional, such courses represent an early integration of photonics into the broader computing curriculum.

Research

The integration of optical computing into digital infrastructure promises significant advancements in research capabilities, enhancing the quality of infrastructure, computational tools, and processing power. Optical systems might enable faster, more energy-efficient data centres and clusters, which are vital for data-intensive fields such as climate science, genomics, particle physics, and AI. A hybrid electronic-photonic approach enhances simulation performance and energy efficiency, allowing researchers to address difficult-to-tackle challenges, such as high-resolution brain simulations or chemical modelling.

Operations

Photonic integration also enhances data centre operations by promoting sustainability. Optical components consume less energy, produce less heat, and reduce cooling needs, leading to lower costs and higher workload density. In addition, the decrease in energy requirements can lead to less stress for local or regional power networks.

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