In the latest issue of "Nature Photonics", researchers from Columbia University School of Engineering demonstrated a new energy-saving chip that can transmit large amounts of data through fiber-optic cables connecting nodes. Instead of using multiple lasers to produce different wavelengths of light, the chip requires just one laser to produce hundreds of different wavelengths of light that can carry independent data streams simultaneously.
Photonic integrated links driven by Kerr frequency combs.
Image credit: Light Wave Research Laboratory/Columbia University School of Engineering
In data centers and high-performance computers running artificial intelligence programs such as large language models, the amount of data they transfer between nodes is the source of the current "bandwidth bottleneck" that limits the performance and scalability of these systems.
Nodes in these systems can be more than a kilometer apart. These systems transmit data over fiber optic cables because metal wires dissipate electrical signals as heat when transmitting data at high speeds. Unfortunately, when signals are sent from one node to another, a lot of energy is wasted in the process of converting electrical data to optical data (and back again).
The newly developed millimeter-scale system uses wavelength division multiplexing and Kerr frequency comb devices to receive monochromatic light at the input end and generate many new colors of light at the output end. These devices are an ideal source of optical communications, where one can encode independent channels of information for each color of light and propagate them through a single optical fiber. This breakthrough could allow systems to transmit more data without using more energy.
The team designed a novel photonic circuit architecture that allows each channel to encode data independently with minimal interference to adjacent channels. In the experiment, the researchers successfully transmitted 32 different wavelengths of light at a speed of 16 gigabytes per second, with a total single fiber bandwidth of 512 gigabytes per second, and an error rate of less than 1 in 1 trillion bits of data. Bits – reaching incredibly high levels of speed and efficiency. The silicon chip that transmits the data measures just 4 millimeters by 1 millimeter, while the chip that receives the light signal and converts it into electrical signals measures just 3 millimeters by 1 millimeter, both smaller than a human fingernail.
The results demonstrate a feasible path to significantly reducing system energy consumption while increasing computing power by orders of magnitude, allowing AI applications to continue growing at an exponential rate with minimal environmental impact.
Previous article:VIAVI presents its comprehensive test solutions at the 23rd China Optical Network Symposium
Next article:All-optical switch processor a thousand times faster than traditional chips
- Popular Resources
- Popular amplifiers
- Keysight Technologies FieldFox handheld analyzer with VDI spread spectrum module to achieve millimeter wave analysis function
- Qualcomm launches its first RISC-V architecture programmable connectivity module QCC74xM, supporting Wi-Fi 6 and other protocols
- Microchip Launches Broadest Portfolio of IGBT 7 Power Devices Designed for Sustainable Development, E-Mobility and Data Center Applications
- Infineon Technologies Launches New High-Performance Microcontroller AURIX™ TC4Dx
- Rambus Announces Industry’s First HBM4 Controller IP to Accelerate Next-Generation AI Workloads
- NXP FRDM platform promotes wireless connectivity
- WPG Group launches Wi-Fi 7 home gateway solution based on Qualcomm products
- Exclusive interview with Silicon Labs: In-depth discussion on the future development trend of Bluetooth 6.0
- Works With Online Developer Conference is about to start, experience the essence of global activities online
- LED chemical incompatibility test to see which chemicals LEDs can be used with
- Application of ARM9 hardware coprocessor on WinCE embedded motherboard
- What are the key points for selecting rotor flowmeter?
- LM317 high power charger circuit
- A brief analysis of Embest's application and development of embedded medical devices
- Single-phase RC protection circuit
- stm32 PVD programmable voltage monitor
- Introduction and measurement of edge trigger and level trigger of 51 single chip microcomputer
- Improved design of Linux system software shell protection technology
- What to do if the ABB robot protection device stops
- CGD and Qorvo to jointly revolutionize motor control solutions
- CGD and Qorvo to jointly revolutionize motor control solutions
- Keysight Technologies FieldFox handheld analyzer with VDI spread spectrum module to achieve millimeter wave analysis function
- Infineon's PASCO2V15 XENSIV PAS CO2 5V Sensor Now Available at Mouser for Accurate CO2 Level Measurement
- Advanced gameplay, Harting takes your PCB board connection to a new level!
- Advanced gameplay, Harting takes your PCB board connection to a new level!
- A new chapter in Great Wall Motors R&D: solid-state battery technology leads the future
- Naxin Micro provides full-scenario GaN driver IC solutions
- Interpreting Huawei’s new solid-state battery patent, will it challenge CATL in 2030?
- Are pure electric/plug-in hybrid vehicles going crazy? A Chinese company has launched the world's first -40℃ dischargeable hybrid battery that is not afraid of cold
- RT-Thread device framework learning UART device
- Vibration information authentication
- Based in Chengdu, recruitment position: mid-level or senior hardware engineer
- The biggest pain point of WiFi in the past has finally been solved by WiFi7. . .
- Detailed explanation of MSP430f149 header file
- Recommended domestic positive-to-negative LDO chips
- Temperature transmitter hardware framework and schematic diagram
- EEWORLD University ---- Live playback: the most important component of the analog world - Signal chain and power supply: LED driver
- Capacitor selection issues in flyback switching power supplies
- Comparison of the advantages of digital cameras and analog cameras in machine vision system design