AI data centres are pushing compute and network performance to new levels. Thousands of GPUs and other accelerators need to process enormous workloads while continuously exchanging data across increasingly fast networks.
This means AI performance depends on more than the processing power of individual GPUs. It also depends on how efficiently data can move between compute resources and how accurately those resources can be synchronised.
Precision timing supports this infrastructure at three key levels: communication, synchronisation and compute.
Communication: why low jitter matters at higher data rates
AI clusters require very high-speed connections between GPUs, switches, optical transceivers and other network equipment. As data rates increase, the timing margins available for transmitting and receiving each bit become smaller.
The reference clock is therefore critical. Jitter introduces small variations in the timing of the clock signal. At very high speeds, this timing uncertainty can consume valuable signal margin and make reliable data transmission more challenging.
A low-jitter reference clock helps preserve that margin, supporting SerDes, optical transceivers and high-speed switching equipment as networks move towards higher data rates.
Higher reference frequencies are also becoming increasingly important. Rakon's high-frequency ultra-low-jitter XO platform addresses these requirements, with current models operating at 500 MHz and delivering 30 fs RMS phase jitter and ±10 ppm frequency stability over temperature. Planned products will extend the platform to 625 MHz and 1.25 GHz.
Modern AI data centres are highly distributed systems. Accurate timing needs to move through the network, from grandmaster clocks through switches and network interface cards and towards the compute infrastructure.
Timing stability becomes particularly important if the primary timing reference is interrupted. An oscillator with good holdover performance can maintain an accurate local frequency reference until the external reference becomes available again.
Different points in the network therefore require different combinations of frequency stability, phase noise, holdover performance and control.
Rakon addresses these requirements with digitally controlled OCXOs, IC-OCXOs and long-holdover discrete OCXOs.
Timing requirements continue into the compute tray, where stable reference clocks support components such as network interface cards, DPUs and AI accelerators.
Accurate and consistent timing can also support timestamped telemetry across distributed AI infrastructure. This allows system software to compare events occurring across different devices and can help identify where processing or data-transfer delays are occurring.
This is particularly useful in large AI clusters, where slower devices or communication paths can affect the efficiency of a distributed workload. Timing does not make a GPU itself run faster, but it forms part of the infrastructure used to coordinate and monitor the resources around it.
Depending on the application, timing devices may need to balance stability, noise performance, frequency, power consumption and package size. Rakon's portfolio ranges from digitally controlled OCXOs and IC-OCXOs to Niku Ultra Stable TCXOs and compact high-stability TCXOs.
There is no single clock specification that applies throughout an AI data centre.
High-speed optical interfaces place particular emphasis on very low phase jitter and higher frequencies. Network synchronisation requires stability, accuracy and holdover, while timing closer to the compute layer may also require small size, low power and flexible control.
This is why a broad timing portfolio is becoming increasingly relevant as AI infrastructure develops.
Rakon is advancing its timing technology through digital control, high-frequency differential designs, XMEMS resonator technology and proprietary ASIC design. Together, these technologies are extending timing performance towards higher frequencies, greater stability, ultra-low jitter and smaller form factors across communication, synchronisation and compute.
As AI data centres become faster, denser and more distributed, the requirements placed on their timing infrastructure will continue to increase.
Precision timing is a small but fundamental part of that infrastructure. By providing stable, low-noise reference clocks where they are needed, timing technology helps support reliable high-speed communication, network synchronisation and the efficient coordination of increasingly powerful compute resources.
For more information about relevant products for these applications, visit our AI and hyperscale infrastructure timing solutions page.
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