Key Technical Features Port Configuration and Speed
The Quantum-X Photonics switch provides 144 ports of 800 gigabits per second (Gb/s) InfiniBand, based on 200 Gb/s SerDes (serialiser/deserialiser) technology.
Total bandwidth capability of approximately 115.2 terabits per second (Tb/s) per switch (144 ports × 800 Gb/s).
2x faster speeds compared to the previous generation of Quantum switches, making it ideal for high intensity AI workloads.
Faster & More Efficient Computing
Optical Computing: photonic chips use light (photons) instead of electrons, enabling ultra fast data processing with minimal heat generation.
AI Acceleration: photonic neural networks can perform matrix multiplications at the speed of light, drastically improving AI training and inference.
Co-processing with Silicon: Hybrid electronic photonic chips (like those from Ayar Labs, Lightmatter) will enhance traditional CPUs/GPUs with optical interconnects.
Next Generation Data Centers & Telecoms
Optical Interconnects: replacing copper wires with photonic links (e.g. Nvidia’s NVLink over optics) will reduce latency and energy consumption in data centres.
Co-packaged Optics (CPO): integrating photonics directly with processors (e.g. Intel, Broadcom) will boost bandwidth beyond 100Tbps.
6G & LiFi: photonics will enable ultra high speed wireless communication (terahertz frequencies) and light-based LiFi networks.
Quantum Photonics
Quantum Computing: photonic qubits (e.g. PsiQuantum, Xanadu) offer room-temperature operation and scalability for error corrected quantum computers.
Quantum Communication: secure quantum networks (QKD) will rely on photonic chips for unhackable data transmission.
Biomedical & Sensing Applications
Lab-on-a-Chip: photonic sensors can detect diseases (e.g. cancer biomarkers) in real time with high sensitivity.
LIDAR & Imaging: self-driving cars and AR/VR will use ultra-compact photonic LIDAR for precise depth sensing.
Material & Manufacturing Breakthroughs
Silicon Photonics (SiPh): leveraging existing CMOS fabs for cost-effective mass production (e.g. GlobalFoundries, TSMC).
New Materials: lithium niobate (LiNbO3), graphene, and 2D materials will enable faster modulators and detectors.
3D Photonic Integration: stacking photonic layers will increase complexity while keeping footprints small.
Energy Efficiency & Sustainability
Photonic chips consume 10-100x less power than electronic chips for data transfer, crucial for green computing.
Optical computing could reduce the carbon footprint of large AI models and data centres.
Challenges Ahead
Cost & Scalability: while silicon photonics is maturing, exotic materials remain expensive.
Thermal & Packaging Issues: managing heat in tightly integrated photonic electronic systems.
Standardization: industry wide protocols for photonic interconnects are still evolving.
Key players and startups, at present
Intel, IBM, TSMC (Silicon Photonics),Nvidia, Ayar Labs, Lightmatter (AI & HPC),PsiQuantum, Xanadu (Quantum Photonics),Rockley Photonics, Luminous Computing (emerging innovators).
NVIDIA silicon photonics networking switches are available as part of the NVIDIA Spectrum-X Photonics Ethernet and NVIDIA Quantum-X Photonics InfiniBand platforms.
NVIDIA Spectrum-X Photonics switches include multiple configurations, including 128 ports of 800Gb/s or 512 ports of 200Gb/s, delivering 100Tb/s total bandwidth, as well as 512 ports of 800Gb/s or 2,048 ports of 200Gb/s, for a total throughput of 400Tb/s.
“A new wave of AI factories requires efficiency and minimal maintenance to achieve the scale required for next-generation workloads,” said C. C. Wei, chairman and CEO of TSMC. “TSMC’s silicon photonics solution combines our strengths in both cutting-edge chip manufacturing and TSMC-SoIC 3D chip stacking to help NVIDIA unlock an AI factory’s ability to scale to a million GPUs and beyond, pushing the boundaries of AI.”